130+ Supply Chain Software Vendors
Fresh recruits often ask me if Lokad has competitors. My answer? Absolutely—TONS of them! Some are direct rivals, aiming to automate supply chain decision-making just like we do. Others are more like loose peers.
Below, you’ll find my big list of 130+ vendors in the realms of supply chain planning and supply chain optimization. This roundup focuses on software companies (not consulting or pure IT firms) dedicated to supply chain. I am including “systems of reports” and “systems of intelligence,” but skipping generic AI players and typical ERP, WMS, or TMS providers—unless they offer a standalone analytical solution separate from their system of record.
Enjoy!
| Company | Description |
|---|---|
| Dassault Systèmes | Founded in 1981, Dassault Systèmes is a global technology company that develops integrated software solutions for 3D design, simulation, digital manufacturing, and comprehensive supply chain planning and optimization. Evolving from its CAD/PLM origins through strategic acquisitions, the company now offers platforms such as DELMIA Quintiq, which employs advanced mathematical and constraint programming techniques along with a proprietary object‐oriented configuration language to enable detailed scheduling, simulation, and real-time analytics. Its 3DEXPERIENCE framework integrates digital twin capabilities with flexible deployment models—both on-premise and cloud-based—and seamless ERP/MES interoperability to support operational efficiency across diverse industries. |
| 3SC Solutions | 3SC Solutions provides cloud‐based supply chain management software that integrates analytics with operational execution through two primary platforms. Its SCAI platform consolidates diverse supply chain data to enable demand forecasting, integrated business planning, simulation‐driven risk mitigation via digital twin models, standardized data governance, and decarbonization roadmap planning, while its iTMS platform manages shipment lifecycles with real-time planning, tracking, contract and rate management, and automated billing and settlement. Founded in 2012 with offices in Gurugram, Amsterdam, Bengaluru, and Pune, the company applies artificial intelligence and machine learning techniques to transform extensive operational data into actionable insights, with its technical methodologies described in broad public terms. |
| Aera Technology | Aera Technology is a software provider that offers a decision intelligence platform designed to integrate and harmonize enterprise data in real time. Its system continuously aggregates data using a low-impact crawler and consolidates it into a unified decision data model that records context, actions, and outcomes. The platform applies machine learning—supporting both off-the-shelf and customized models—within a cloud-based architecture to analyze data and autonomously execute business decisions through modular, prepackaged tools and a natural language, no-code interface. While it claims to streamline decision-making processes across various business domains, technical specifics remain high-level, suggesting the need for cautious evaluation of its cognitive automation and continuous learning assertions. |
| Agents of AI | Agents of AI develops modular software agents that aim to automate and optimize diverse business operations including supply chain coordination, customer relationship management, lead management, negotiation, energy efficiency, human resources, risk analysis, and fraud detection. The company employs techniques such as machine learning, natural language processing, and predictive analytics to continuously analyze real-time data and facilitate autonomous decision-making and routine task automation. Its offerings are described through detailed use-case articles that outline workflows like inventory management and customer data evaluation, while technical specifics regarding the underlying algorithms, system integration, and deployment methodologies remain minimally disclosed. |
| AIMMS | AIMMS provides prescriptive analytics and optimization solutions that enable organizations to build and deploy custom mathematical models addressing complex decision-making challenges across industries such as supply chain, production planning, and logistics. Founded in 1989 as Paragon Decision Technology, the company has evolved to offer a platform built around a declarative algebraic modeling language and multiple high-performance solvers, available via both on-premise deployments and secure, containerized cloud solutions on Microsoft Azure. Its low-code environment simplifies the development of optimization applications for non-technical users, while also supporting integrations with external machine learning tools and exploratory AI functionalities for enhanced scenario analysis. |
| Agentic AI | Agentic AI develops autonomous multi‐agent systems for inventory management and demand forecasting by leveraging predictive analytics, machine learning, and large language models to process historical, real‐time, and market data. Its platform coordinates specialized agents—such as those for demand prediction, automated stock reordering, and risk assessment—via orchestration frameworks and API integrations with existing ERP systems, thereby enabling automated decision workflows while relying on industry‐standard technical components and limited publicly disclosed algorithmic details. |
| Algonomy | Algonomy, established in 2004, is a cloud‑based SaaS platform that unifies disparate customer and operational data through an ensemble of traditional statistical forecasting, supervised, and unsupervised machine learning techniques. Its solution integrates multiple retail data sources into dynamic customer profiles, enabling real‑time personalization, targeted omnichannel marketing, and inventory optimization. The platform leverages a suite of modules designed for automated decisioning—from personalized recommendations to replenishment planning—while providing scalable connectivity with pre‑built interfaces to existing retail systems. |
| Anaplan | Anaplan is a cloud-based enterprise planning provider established in 2006 that develops a connected planning platform enabling integrated decision-making across finance, supply chain, sales, and HR. Its solution uses a proprietary in-memory calculation engine (Hyperblock) to model complex, multidimensional data while consolidating inputs from diverse sources, and it employs robust application lifecycle management—including a secured deployed mode—to maintain production integrity. The platform also integrates established forecasting algorithms and linear programming optimization techniques to analyze numerous business scenarios and evaluate trade-offs, all executed through standardized data integration processes and conventional computational methods. |
| Antuit.ai | Antuit.ai, founded in 2013 and now part of Zebra Technologies, offers a cloud-native SaaS platform for the retail, consumer products, and manufacturing sectors that leverages advanced machine learning to produce probabilistic demand forecasts—capturing full statistical distributions—and applies stochastic optimization to compute profit‐optimal inventory levels based on detailed cost, margin, and supply chain data; the platform integrates with existing ERP and order management systems via API connections to support inventory replenishment, pricing, and merchandising decisions while enabling rapid, scalable deployment in environments characterized by demand uncertainty. |
| AnyLogic | AnyLogic is a simulation modeling platform that enables users to build dynamic representations of complex systems by supporting multiple methodologies—agent-based modeling, discrete event simulation, and system dynamics. It facilitates the creation of digital twins by integrating detailed simulation models with real-time or historical operational data, allowing for scenario testing and data-driven analysis through interactive dashboards and customizable outputs. Built on a Java SE and Eclipse-based framework, it allows for extensive customization using Java code while offering cloud-based deployment options for scalable and collaborative simulation experiments, and it integrates external machine learning tools such as H2O.ai to supplement predictive analytics without relying on a proprietary AI engine. |
| anyLogistix | anyLogistix is a supply chain analytics platform that combines dynamic simulation with analytical optimization to support network design, inventory management, and risk evaluation. It leverages the AnyLogic simulation engine for agent‐based, discrete event, and system dynamics modeling alongside IBM CPLEX for solving linear and mixed‑integer programming problems. The platform converts optimization results into digital twin simulations, enabling detailed “what‑if” scenario analyses and real‑time performance monitoring, and is evolving from a Windows‐based desktop application to a hybrid client‑server and cloud‑integrated environment to enhance collaborative decision–making. |
| Arkieva | Arkieva is a software vendor that delivers integrated supply chain planning solutions by consolidating data from diverse enterprise systems through a proprietary Data Connector. Its Arkieva Orbit platform employs an in-memory processing engine to support both transactional and analytical operations, enabling real‑time simulation, detailed scenario analysis, and forecasting. The solution addresses demand, inventory, and supply planning challenges using a combination of rule‑based decision support and statistical forecasting methods, and is implemented via rapid iterative prototyping with flexible deployment options across on‑premise, cloud, or hybrid environments. |
| Artisans Cloud | Artisans Cloud develops a unified retail and commerce platform that integrates functions such as supply chain planning, merchandising, inventory management, order routing, and fulfillment through a cloud-native, modular architecture; the platform is built on a composable, microservices-based, API-first, headless design that supports flexible integration with diverse enterprise systems, and it incorporates AI and machine learning capabilities for predictive analytics and process automation, although publicly available technical details on these features remain limited. |
| Asper.ai | Asper.ai, established in 2022 under Fractal Analytics, delivers a cloud‐based SaaS platform known as Dynamic Demand.ai that aggregates internal data—including historical sales, inventory levels, and promotional calendars—with external signals such as holidays and macroeconomic indicators to produce near-final, explainable forecasts; the solution employs machine learning algorithms to capture complex, nonlinear interactions, automates low-risk decision processes, and integrates with legacy Sales & Operations Planning systems via scalable AWS infrastructure to support demand optimization in the consumer goods and retail sectors. |
| aThingz | aThingz delivers an integrated, cloud‑based supply chain platform that unifies logistics planning, execution, and financial analysis through a modular microservices architecture; the system ingests diverse data formats from legacy and modern sources to provide real‑time transportation tracking, spend visibility, demand forecasting, and cost‑to‑serve analysis by applying proven optimization techniques—such as linear programming and rule‑based heuristics—within a continuous, closed‑loop feedback process. |
| Atoptima | Atoptima is a software editor specializing in mathematical optimization for complex operations planning in logistics, supply chain management, and production scheduling. Drawing on decades of academic research in operations research, the company applies deterministic algorithms—including mixed-integer programming, branch‑and‑price, and decomposition techniques—to develop modular, cloud‑based solvers that address challenges like vehicle routing, container packing, warehouse order processing, and resource allocation. Its solutions are designed to integrate with existing enterprise systems via native APIs, translating rigorous academic methods into practical, scalable decision‑support tools for industrial applications. |
| B2WISE | B2WISE develops cloud-based supply chain planning software built on Demand Driven Material Requirements Planning (DDMRP) principles, enabling organizations to shift from traditional, forecast-based MRP systems to adaptive, demand-driven operations. The solution integrates ERP connectivity with modules for demand and supply planning, advanced forecasting using heuristic and tournament techniques, capacity planning, and real-time production scheduling, all deployed on a multi-regional AWS serverless architecture. Supplemented by training and consulting services, B2WISE unifies disparate data sources into a cohesive planning framework designed to respond to changing customer demand and optimize inventory and production decisions. |
| Blue Ridge Global | Blue Ridge Global delivers a cloud-based supply chain management suite that integrates demand forecasting, replenishment planning, supply planning, and integrated business planning to optimize inventory levels and pricing. The platform collects historical and real-time data through pre-built ERP connectors, leveraging an AI-assisted forecasting engine that analyzes market trends, production constraints, and sales signals to generate SKU-level forecasts and automated replenishment recommendations. Its modular, cloud-native architecture supports rapid deployment and continuous operational adjustments, complemented by dedicated advisory LifeLine support that facilitates cross-departmental planning and alignment, all implemented using standard industry practices with proprietary AI/ML details remaining undisclosed. |
| Blue Yonder | Blue Yonder provides comprehensive digital supply chain management solutions that integrate demand forecasting, inventory optimization, replenishment, and transportation management into a unified data cloud platform. It supports both on-premise and cloud-hosted deployments to facilitate real-time coordination among over 150,000 trading partners while transforming extensive operational data into predictive insights using established AI and machine learning techniques with modern data frameworks. Its methodology centers on rigorous system integration and data-driven processes to optimize multi-enterprise supply chain execution while maintaining transparency, data security, and human oversight. |
| Board International | Board International delivers an integrated enterprise planning platform that unifies business intelligence, corporate performance management, and predictive analytics. The solution consolidates financial and operational planning by combining dashboards, reporting, budgeting, forecasting, and simulation within a low-code graphical environment. Its technology employs a hybrid in-memory engine that blends disk-based and in-memory processing for efficient multidimensional calculations, while interfacing with Microsoft technologies to support secure, scalable deployments via cloud or on-premises models. Additionally, the platform incorporates external AI and machine learning services to provide predictive insights that integrate internal performance data with real-time economic indicators. |
| Bright Insights | Bright Insights operates an AI-driven platform that combines proprietary, high-frequency public web data collection with robust in-house cleansing, structuring, and matching processes to generate real-time, actionable insights across both regulated digital health products and retail/eCommerce markets. The cloud-based solution, deployed in multiple countries and integrated via APIs with detailed dashboards and alert systems, supports analytics for price intelligence, SKU tracking, inventory optimization, and competitive analysis. While the company emphasizes advanced machine learning techniques, its publicly available technical details remain high-level and primarily marketing-oriented, providing limited insight into the specific methodologies employed. |
| C3.ai | C3.ai is an enterprise software provider that develops a platform for building, deploying, and operating AI applications aimed at optimizing processes such as industrial operations, process control, and supply chain management. The platform uses a model‑driven architecture to integrate disparate data—ranging from legacy systems to real‑time operational sensors—into reusable models that incorporate principles from conventional machine learning, physics‑based modeling, and established software engineering. Its solutions support on‑premise, multi‑cloud, and edge deployments by leveraging standard cloud infrastructures and open‑source tools, while its efficiency and scalability claims continue to be evaluated independently. |
| ClearOps | ClearOps is a B2B SaaS provider that offers a platform for aftersales and supply chain management in the machinery industry by integrating data from ERP, dealer management, and IoT systems through pre-built connectors. The platform uses machine learning for predictive demand forecasting and automated parts ordering while employing AI-driven governance—combining generative AI with retrieval-augmented generation—to perform risk assessments and compliance reporting, thereby centralizing information and streamlining traditionally fragmented processes. |
| Colibri | Colibri offers an AI-powered, cloud-based Sales & Operations Planning platform that replaces manual, spreadsheet-driven methods with a suite of integrated modules for demand forecasting, supply planning, and strategic alignment. Built on Microsoft Azure, the solution centralizes data from multiple business functions to enable real-time collaboration, automate routine tasks using machine learning techniques, and support ERP integration with established security protocols, while the technical details provided remain succinct and follow industry-standard practices. |
| COMET Analysis | COMET Analysis is a technology firm offering a comprehensive, cloud‐based suite of digital solutions designed to support incident investigations, audits, and supply chain risk management. The platform employs a structured root cause taxonomy with designated Root Maps to systematically capture immediate causes and underlying systemic issues, while providing streamlined modules such as a rapid “COMET Lite” process for low-potential risks. Its integrated approach includes dynamic dashboards powered by standard enterprise tools like Microsoft Power BI and an AI-driven module that uses machine learning and natural language processing to extract actionable insights from both structured and unstructured HSEQ data. Furthermore, the company’s Software-as-a-Service model consolidates data across disparate sources, automates compliance notifications, and facilitates agile deployment without extensive local infrastructure requirements. |
| Coupa Software | Coupa Software provides a cloud-native Business Spend Management platform that centralizes and automates key financial processes—including procurement, invoicing, expense management, contract and supplier management, and supply chain planning—using a scalable, no-code SaaS architecture. The system integrates rule-based analytics and machine learning with community-driven data aggregation to extract actionable insights, streamline workflows, and facilitate seamless integration with existing ERP systems, all while supporting regulatory compliance and operational efficiency. |
| Daybreak | Daybreak is an enterprise technology company that provides automated supply chain planning solutions by integrating data ingestion, cleansing, and domain‑specific feature engineering with a diverse set of machine learning and statistical models to generate forecasts. Its platform comprises an AI Prediction Platform for automating raw data processing, an AI Decision System that combines algorithmically generated forecasts with structured human input through an interactive dashboard that offers explainability, and Luma, a digital planning assistant that uses natural language interactions to support adaptive problem‑solving. Delivered as a cloud‑based SaaS solution leveraging containerization, Daybreak is designed to integrate with existing ERP and APS systems while continuously refining its approach through the incorporation of human decision overrides, although independent validation of its performance improvements remains ongoing. |
| DecisionBrain | DecisionBrain, founded in 2013 and headquartered in Paris with additional international offices, develops decision support software that addresses complex challenges in operational planning, scheduling, logistics, supply chain management, and workforce optimization. The company employs a modular low-code platform that enables rapid configuration of tailored solutions, an optimization engine capable of handling computationally intensive tasks with support for multiple industry-standard solvers, and a configurable web interface that facilitates scenario management and explainable decision-making. By integrating established mathematical optimization techniques with statistical forecasting and machine learning methods, DecisionBrain delivers scalable systems deployable on local, on-premise, or cloud infrastructures to support critical business processes. |
| DeepVu | DeepVu is a software company that provides an AI-assisted supply chain planning platform, employing reinforcement learning–based decision agents, digital twin simulations, and a comprehensive knowledge graph to integrate historical, real-time, and external data for optimizing demand planning, production scheduling, procurement, and logistics; the platform is offered as a modular SaaS solution that integrates with established ERP systems via APIs and utilizes cloud infrastructures for continuous data processing while retaining human oversight in final decisions, even though detailed public performance metrics and independent validations remain limited. |
| DemandCaster | DemandCaster is a cloud-based supply chain planning solution that assists manufacturing companies in transitioning from manual, spreadsheet-driven methods to integrated, automated planning workflows. It facilitates demand forecasting, inventory optimization, and supply planning by consolidating real-time data from ERP systems and enabling bidirectional integration with platforms such as Oracle NetSuite. The solution incorporates a machine learning forecast manager to refine predictive accuracy alongside traditional statistical techniques and is delivered as a SaaS component within the Plex Manufacturing Cloud following its 2016 acquisition by Plex Systems. Public disclosures offer limited details on its underlying technology stack and algorithmic methodologies. |
| Demand Driven Technologies | Demand Driven Technologies is a provider of supply chain planning solutions that combines demand-driven planning (DDMRP) with AI/ML capabilities through its platform, Intuiflow. The platform offers modules for materials management, sales and operations planning, scheduling, and demand forecasting, and supports both cloud-based and on-premise deployments with integration to ERP systems such as NetSuite. Founded in 2011 in Atlanta, GA, the company serves a diverse range of industries—from automotive to healthcare—employing a rapid and modular deployment strategy, although public disclosures provide limited technical detail on the underlying AI/ML algorithms. |
| Dista.ai | Dista.ai is an AI-enabled, low-code/no-code location intelligence platform that offers a suite of SaaS applications designed to streamline and automate field operations for large enterprises. Its products support functions such as automated lead assignment, sales territory mapping, route optimization, delivery management, and asset tracking by converting raw location data into actionable insights using a proprietary geocoding engine and cloud-based mapping services. The platform provides configurable dashboards, flexible API integrations, and offline mobile capabilities, and is deployed via an 80-20 productized model that delivers standard out-of-the-box functionality alongside tailored solutions for sectors including financial services, retail, logistics, and pharmaceuticals. |
| E2open | E2open is a cloud-based, end-to-end supply chain management platform that integrates demand planning, logistics, global trade compliance, and channel management by connecting over 400,000 trading partners through a modular SaaS solution built on a microservices architecture with ERP connectors and API integrations; it leverages technologies such as Java, Spring, and modern web frameworks to enable rapid deployment and real-time operational visibility while incorporating artificial intelligence for functions like demand sensing and inventory optimization, though specifics on its AI methodologies remain limited. |
| EdgeVerve Systems | EdgeVerve Systems, a subsidiary of Infosys established in 2014, develops integrated enterprise software platforms that enable digital transformation across sectors such as banking, supply chain, and insurance. Its portfolio comprises the Finacle core banking solution, AssistEdge robotic process automation framework, XtractEdge document intelligence system, TradeEdge supply chain integration solution, and an AI Next platform for applied AI. The company’s solutions are engineered on a modern technology stack based on Java microservices, RESTful APIs, and cloud-agnostic architectures, emphasizing modular design, flexible deployment, and strategic integration while public technical disclosures remain high-level. |
| Elixum | Elixum, now part of Accenture, builds on over 25 years of supply chain planning experience from the Camelot Group to offer its Supply Chain Avatar platform—a cloud-native, multi-tier solution that integrates a unified core model with a planning engine based on an in-memory hybrid graph data model, a cognitive engine employing pre-built machine learning skills for decision automation, and an optimizer engine supporting state-of-the-art solvers. The platform is engineered using modern software practices such as microservices, containerization, and agile methodologies to support both centralized and decentralized operations with real-time scenario simulation, though its advanced AI and ML capabilities await further independent technical validation. |
| eLogii | eLogii is a cloud-based SaaS platform that automates and optimizes last-mile delivery, field service, and logistics operations by employing deterministic, rule-based algorithms complemented with data‐driven elements to compute efficient routes. The platform utilizes a dual-engine system featuring a fast default engine that processes historical and real-time traffic data and an advanced engine that offers customizable load-balancing and clustering techniques, enabling precise route planning and dynamic re-optimization as conditions change. It provides a web dashboard for planners and mobile applications for drivers, supports real-time tracking and comprehensive analytics, and integrates via APIs and CSV imports with external systems such as CRM and ERP while adhering to a cloud-first, highly configurable deployment model. |
| Epicor Software Corporation | Epicor Software Corporation, founded in 1972 and based in Austin, Texas, delivers enterprise resource planning (ERP) solutions for manufacturing, distribution, retail, and service industries through a modular suite of products such as Epicor iScala, Epicor Kinetic, and Epicor Prophet 21. Its platform integrates core business functions including financial management, production planning, supply chain coordination, and customer relationship management, while supporting both on-premises and cloud deployments. The company employs robust data integration techniques—such as asynchronous event streaming via a Data Fabric—and incorporates machine learning tools to enhance forecasting, budgeting, and inventory planning, all implemented through a structured methodology that enables scalable and customizable solutions. |
| Factible Tools | Factible Tools is a provider of a cloud-based software platform that supports the design, planning, and optimization of supply chain networks by enabling users to define facility locations, capacities, and service level trade-offs through mathematical optimization techniques developed over decades of industry experience; the solution accepts structured data inputs via Excel templates and generates interactive visualizations, dashboards, and scenario analyses within a cloud-native SaaS framework designed for scalability and global access, while maintaining limited public disclosure on the specific technical and AI/ML methodologies employed. |
| Flowlity | Flowlity provides a cloud-based SaaS platform for automated supply chain planning and forecasting that integrates historical MRP data with probabilistic forecasting, simulation-based scenario analysis, and machine learning techniques to produce actionable recommendations such as dynamic inventory bounds and disruption alerts. The platform complements existing ERP/MRP systems by offering multiple forecast scenarios and decision-support insights rather than fully automated decision-making, thereby enabling supply chain managers to adjust inventory levels and mitigate risks. Founded by professionals with expertise in applied mathematics and supply chain operations, Flowlity focuses on enhancing traditional forecasting methods through integrated AI-driven analytics, although the detailed technical implementation remains limited in publicly available documentation. |
| FourKites | FourKites offers a cloud‐based subscription platform that delivers real‑time global supply chain visibility by integrating data from telematics, GPS sensors, and enterprise systems to create dynamic digital twins of shipments, orders, assets, and inventory. It employs a modern microservices architecture on scalable cloud infrastructure to process millions of daily events and to support multi‑modal transportation tracking across road, rail, ocean, and air. The platform uses predictive analytics and rule‑based automation—including emerging natural language interfaces—to provide proactive insights and support rapid carrier onboarding and disruption management without relying on unverified “AI‑powered” claims. |
| FuturMaster | FuturMaster, established in 1994, provides a SaaS-based platform designed for comprehensive supply chain planning and revenue growth management. Its flagship Bloom Platform integrates long-term strategic planning with mid- and short-term operational scheduling by consolidating demand forecasting, inventory management, production and procurement planning, and trade promotion optimization. The solution employs AI and machine learning for large-scale forecasting and demand shaping, utilizes digital twin models and global optimization algorithms for scenario analysis and coordinated planning, and is built on modern cloud infrastructure and web technologies to support scalable, multi-regional operations. |
| GAINSystems | Founded in 1971 and headquartered in Chicago, GAINSystems delivers a modular, cloud-hosted platform that addresses supply chain planning and optimization through integrated solutions for demand forecasting, inventory management, replenishment, and multi-echelon network design. The system harnesses a blend of advanced analytics, simulation, and elements of AI and machine learning—implemented with conventional operations research techniques and proprietary heuristics—to enable real‑time data exchange with ERP systems via its GAINS Connect API, ensure rapid project deployment, and support continuous network optimization, while its acquisition initiatives underline a commitment to enhancing decision engineering capabilities. |
| Ganacos | Ganacos is a French software company founded in 2016 that offers a cloud-based SaaS platform unifying sales, operations, and financial planning for mid- to large-sized enterprises. Its system consolidates data from ERP systems, spreadsheets, and other sources into a familiar Excel-like interface, while a proprietary OLAP engine and its specialized calculation language, Chulengo, perform rapid, multidimensional analyses and “what-if” scenario simulations using advanced statistical forecasting techniques. This approach enables collaborative, data-driven decision making by ensuring data integrity, traceability, and timely insights across diverse operational and financial functions. |
| GEP | GEP delivers cloud‐native procurement and supply chain solutions by integrating software, consulting, and managed services into its proprietary GEP QUANTUM platform, built on Microsoft Azure using microservices and low‐code tools for rapid deployment and scalable integration. Its portfolio covers procurement, spend analytics, supply chain management, and accounts payable automation with machine learning techniques applied to demand forecasting, supplier evaluation, and invoice processing, while strategic acquisitions of firms like OpusCapita and COSTDRIVERS have expanded its capabilities in electronic invoicing and cost forecasting. The company’s SaaS delivery model with pre‐packaged APIs enables integration with established ERP systems, providing organizations a structured approach to digitalizing their procurement and supply chain operations. |
| Getron | Getron, founded in 2003, develops a suite of AI-based software solutions focused on inventory management, supply planning, and order processing for sectors such as retail, healthcare, manufacturing, energy, and automotive. Its offerings include tools for prescriptive stock transactions, demand forecasting, diagnostic analytics, and cost and pricing recommendations—all designed to optimize the inventory lifecycle. The company employs a proprietary data structure and a no-code Mass Customization Interface to integrate and transform raw data efficiently, while its cloud-native SaaS/PaaS model on Microsoft Azure supports rapid deployment and streamlined integration with customer ERP systems. Additionally, the platform claims to leverage explainable AI to generate actionable work orders with transparent decision logic, although detailed technical methodologies remain limited in public disclosures. |
| GMDH Software | GMDH Software is a global provider of supply chain and integrated business planning solutions that leverages the Group Method of Data Handling—a self-organizing, iterative polynomial modeling technique developed in the late 1960s—to forecast demand and optimize inventory planning. The platform systematically divides historical data into training and validation sets, automatically generates candidate polynomial models, and uses error minimization criteria for objective model selection. It integrates with various ERP systems via bi‑directional connectors and APIs, offering a data‑driven framework that emphasizes mathematical robustness and reproducibility over modern deep learning architectures. |
| GoComet | GoComet is a cloud-based, AI-powered supply chain automation platform that integrates key international logistics functions through specialized modules for freight procurement, real-time container tracking using AIS and geofencing data, invoice reconciliation with intelligent OCR and language processing, and centralized shipment management via a Logistics Control Tower. The platform is built on modern web technologies with a scalable SaaS architecture and standardized APIs for ERP integration, while its proprietary machine learning techniques support predictive analytics and market rate indexing. Founded in 2016 in Singapore by IIT graduates, GoComet consolidates diverse logistics processes into a unified system that delivers transparent, data-driven insights to address inefficiencies in global freight management. |
| Goflow | Goflow provides a cloud‐based SaaS platform that unifies multi‐channel e-commerce operations by consolidating order and inventory management, shipping logistics, and inventory forecasting into a single real-time dashboard. The system integrates data across hundreds of sales channels and over 250 third-party services using RESTful APIs and technologies like C# and .NET, and it automates purchasing recommendations through statistical models that analyze historical and live sales data. Additionally, its direct printer communication avoids typical browser constraints to deliver rapid and efficient data processing. |
| IBM | IBM is a multinational technology company that designs, manufactures, and supports a broad range of hardware, software, and technology services, including enterprise performance management solutions like IBM Planning Analytics. With roots in decades‑old in‑memory, multidimensional OLAP technology originally developed as TM1, IBM offers integrated planning, budgeting, forecasting, and scenario analysis capabilities by leveraging rule‑based calculations and flexible deployment options such as on‑premises, hybrid, and cloud configurations. Its platforms are engineered with distributed, multi‑tier architectures and extensive API integrations that enable rapid processing of complex data models and real‑time insights, while incremental AI‐driven enhancements—grounded in established statistical methods—facilitate natural language querying and automated forecasting to support collaborative, data‑driven decision‑making across organizations. |
| Ikigai Labs | Ikigai Labs is an enterprise software vendor that develops a platform for transforming structured, tabular data into actionable insights. The platform uses Large Graphical Models to reconcile data, forecast trends, and simulate what‑if scenarios, integrating a low‑code/no‑code interface with robust APIs to serve both business users and technical teams. It supports flexible deployment—including SaaS, cloud, and on‑premise solutions—and offers pre‑built connectors for diverse data sources, while incorporating expert‑in‑the‑loop mechanisms that allow human oversight in decision-making. Founded by academics and entrepreneurs with MIT ties, the company’s approach focuses on leveraging statistical dependencies in data to streamline enterprise forecasting and planning. |
| Impact Analytics | Impact Analytics provides cloud-based analytics solutions for the retail industry that replace conventional spreadsheet methods with integrated AI-enhanced tools. Founded in 2015, the company delivers a range of applications covering demand planning, inventory and merchandising optimization, and dynamic pricing, all built on machine learning models that analyze historical, real-time, and external data to produce adaptive forecasts and actionable insights. Its software-as-a-service platform emphasizes rapid deployment and seamless integration with existing operational systems, although detailed technical documentation and performance metrics are limited. The company’s approach is substantiated by notable funding and strategic initiatives, reflecting a market focus on data-driven retail optimization. |
| Infor | Infor is a global enterprise software company that develops integrated solutions for supply chain and ERP operations, combining modules for inventory control, order and warehouse management, demand planning, and transportation logistics. Founded in 2002 and expanded through a series of acquisitions, the company employs a unified data model and middleware frameworks to connect disparate business functions and offer both cloud-based and on-premise deployment options. Its approach utilizes a mix of proprietary and open-source technologies, with carefully presented AI and automation features designed for predictive analytics and streamlined operational management across diverse industries. |
| INFORM Software | INFORM Software, founded in 1969, develops supply chain optimization solutions that integrate demand forecasting, inventory management, and production scheduling through a unified software platform. Its product ADD*ONE leverages established operations research techniques and adaptive forecasting methods—combining traditional optimization algorithms with iterative, data-supported adjustments—to generate actionable planning recommendations. The system interfaces with major ERP platforms via certified connectors and is available both as on-premise and cloud-based deployments, enabling organizations to automate routine planning tasks and standardize data processes without overstating its AI capabilities. |
| Intelligent Audit | Intelligent Audit, founded in 1996 and based in Rochelle Park, New Jersey, provides a cloud-based SaaS platform that automates freight and parcel invoice auditing, recovery, and data analytics by verifying transportation invoices against contractual terms using over 150 systematic audit checks and proprietary machine learning for real‑time anomaly detection. The platform integrates with major carriers and transportation management systems to normalize large volumes of shipping data, supports simulation and optimization tools for forecasting costs and managing carrier contracts, and offers advanced reporting and contract management features that help users identify discrepancies and streamline logistics operations. |
| InterDynamics | Founded in 1992, InterDynamics develops simulation-based decision support and fatigue risk management solutions by utilizing its discrete-event simulation engine, Planimate, to convert operational data into animated, interactive visualizations that aid in planning, scheduling, and resource allocation across sectors such as rail logistics, supply chain, port operations, and healthcare. The company further integrates scientifically validated biomathematical models with risk engineering methodologies to assess and mitigate fatigue-related risks in shiftwork environments, delivering tailored solutions through iterative prototyping that combines legacy systems with modern API-driven integrations. Its approach relies on structured, rule-based simulation rather than autonomous machine learning, enabling detailed what-if analyses for operational decision-making. |
| Intuendi | Intuendi provides a cloud-hosted platform for demand forecasting and inventory optimization designed for small and medium enterprises. It uses a combination of classical statistical methods and machine learning techniques—including regression models, neural networks, and online learning—to analyze historical sales data together with external factors such as promotions, seasonality, and market trends. By integrating top-down and bottom-up forecasting approaches, the system continuously updates predictions and issues automated purchase order recommendations while enabling ERP integration via APIs and secure FTP. Developed by engineers and researchers from the University of Florence, the subscription-based solution focuses on systematic data processing and feature engineering to enhance supply chain efficiency under complex market conditions. |
| Inventory Path | Inventory Path is a cloud‑based, modular inventory and ERP platform that consolidates inventory control, point‑of‑sale management, order processing, shipping, and returns into a single system. It continuously tracks stock levels in real time using automated data capture and employs machine learning for predictive analytics and process automation, while also integrating augmented reality interfaces to overlay digital information on physical warehouse environments for enhanced inventory verification. Offered as a subscription‑based SaaS with modular components adaptable to various business needs, the platform centralizes operational data along the supply chain, though detailed technical documentation on its architecture and integration methods is limited. |
| John Galt Solutions | John Galt Solutions is a US-based provider of forecasting and supply chain planning software established in 1996 that delivers products such as ForecastX—a one‐click forecasting tool integrated with Microsoft Excel—and the Atlas Planning Platform, a cloud-based and hybrid solution designed for end-to-end supply chain management. The company aggregates historical, real-time, and external data to support demand forecasting, inventory management, and coordinated supply chain operations; it employs probabilistic planning methods and machine learning techniques alongside natural language query interfaces and low-code deployment options to integrate with existing ERP and cloud systems using a conventional modern web technology stack. |
| Kaleris | Kaleris is a provider of cloud‐based supply chain execution and visibility solutions that integrate yard management, transportation logistics, terminal operations, and maintenance into a unified platform. Established in 2004, the company utilizes sensor technologies such as RFID and GPS to automate and monitor essential processes like truck scheduling, gate check‐ins, load tracking, and berth planning. Its system aggregates operational data from various sources into centralized dashboards using cloud analytics, standardized APIs, and a multi‐tenant design, thereby facilitating interoperability with existing enterprise systems while emphasizing efficient, rule‐based automation over unverified claims of fully adaptive AI/ML capabilities. |
| Kardinal.ai | Kardinal.ai is a software company founded in 2015 that offers a cloud-based SaaS platform for last mile delivery optimization. The platform employs combinatorial optimization algorithms and machine learning techniques to process real-time data from driver mobile applications, traffic conditions, and operational constraints, dynamically planning and adjusting delivery routes. By integrating with existing logistics systems via APIs, it provides continuous decision support and iterative re-optimization, aiming to enhance resource allocation and reduce operational costs in complex and ever-changing delivery environments. |
| KetteQ | Founded in 2018 in Atlanta, GA, KetteQ develops cloud-based adaptive supply chain planning solutions that dynamically simulate thousands of decision scenarios in real time to support demand forecasting, inventory and production planning, and cross-functional collaboration. The platform uses its patent-pending PolymatiQ™ solver to adjust planning parameters automatically through AI and machine learning techniques that integrate internal data with external economic indicators, while leveraging established infrastructures like Salesforce and AWS. Built on a modern technology stack including Java, Spring Web MVC, and PostgreSQL, KetteQ’s SaaS solution is engineered for scalability and rapid deployment, though detailed technical documentation and independent validation of its performance remain limited. |
| Kimaru.ai | Kimaru.ai is a Tokyo‐based enterprise software company founded in 2023 that delivers a decision intelligence platform for retail and supply chain management by automating data ingestion and transformation, applying machine learning and optimization techniques to generate actionable recommendations for inventory, pricing, and logistics, and incorporating a human‐in-the-loop interface to enable real-time operational decision making; the platform is engineered in Python and containerized with Docker for scalable cloud deployment, addressing traditionally manual and error‐prone processes through a structured, data-driven workflow. |
| Kinaxis | Kinaxis is a Canadian software vendor that provides a cloud‐based supply chain orchestration platform enabling rapid, concurrent planning across procurement, manufacturing, and logistics. Founded originally as a hardware‐simulation and MRP tool in 1984 and rebranded in 2005, it employs highly optimized in‐memory computing and an agile SCRUM-based implementation methodology to support iterative deployments and fast time-to-value. The platform, marketed under the Maestro name as an AI-infused solution, integrates automated data ingestion, demand forecasting, and natural language interfaces while incorporating strategic acquisitions like Rubikloud and MPO to extend its capabilities to real-time multi-party execution within a scalable, subscription-based framework. |
| Koerber Digital | Koerber Digital is the dedicated digital business unit of the Koerber Group, established in 2017 to drive digital transformation in manufacturing and supply chain industries. The company delivers machine-agnostic SaaS solutions that integrate cloud-based systems, AI, machine learning, and real-time data analytics with existing production infrastructures. Its approach leverages agile innovation cycles and plug-and-play interfaces to seamlessly connect with legacy systems, ensuring that digital concepts are rigorously validated and scaled to enhance overall equipment effectiveness and optimize supply chain execution. |
| Infios | Infios is a rebranded supply chain execution platform that integrates order management, warehouse management, and transportation management into a unified modular system. It offers deployment as SaaS or on-premises, utilizing configurable event automation and simulation tools to optimize warehouse layouts and process flows, while its recent acquisition bolsters multimodal freight capabilities. Built on the Körber One architecture, the platform provides end-to-end visibility and interoperability across supply chain functions, relying on established analytical methods and mature software practices rather than unverified advanced AI innovations. |
| Lanner | Lanner is a simulation software company that develops digital twin solutions and discrete event simulation tools to model, analyze, and optimize complex supply chain networks. Its approach constructs detailed virtual replicas of real-world processes—integrating decades‑old simulation foundations with modern Java‑based platforms—to run comprehensive “what‑if” scenario analyses, quantify performance metrics like throughput and lead times, and identify operational bottlenecks. The solution is designed to work in tandem with existing ERP and MES systems, relying on high‑quality input data and expert interpretation to provide decision‑support insights rather than automated resolutions. |
| LeanDNA | LeanDNA, founded in 2014, develops a cloud-based supply chain execution platform for discrete manufacturers in sectors such as automotive, aerospace, industrial, and medical by integrating ERP data through its lightweight Connect tool into a universal data model that underpins real-time dashboards, inventory monitoring, shortage management, and prescriptive analytics; the platform’s technical details—particularly regarding its AI and machine learning capabilities—remain minimally disclosed, emphasizing a data aggregation and rule-based approach rather than detailed algorithmic transparency. |
| Locate2u | Locate2u is a SaaS platform that streamlines delivery and service operations by automating route planning, dispatch management, and real-time fleet tracking through a cloud-based, API-first system. Initially evolving from Zoom2u and expanded via strategic acquisitions such as a Local Delivery Shopify App and Talcasoft, the platform integrates features like GPS tracking, driver apps, and proof-of-delivery modules to address logistical challenges. Although it references AI/ML enhancements, its technical documentation suggests reliance on established optimization algorithms and conventional methods rather than extensively detailed innovative practices. |
| Locus | Locus is a logistics technology provider that offers a modular, cloud-native, API-first suite of software solutions designed to manage the entire order-to-delivery process—from order capturing and dispatch planning to automated fulfillment, delivery orchestration, capacity management, and real-time tracking. The platform integrates interconnected algorithms, including proprietary geocoding and machine learning techniques, to optimize routes based on over 180 operational constraints such as time, distance, vehicle specifications, and traffic conditions, while maintaining interoperability with legacy systems like TMS, WMS, ERP, and CRM and adhering to international security standards through robust encryption and compliance certifications. |
| Logility | Logility is a supply chain planning and analytics provider that delivers an integrated platform for demand forecasting, inventory optimization, product lifecycle management, and order execution. The company employs a mix of machine learning algorithms, statistical methods, and rule-based automation to process real-time data and continuously adjust operational parameters, supporting both cloud-hosted and on-premise deployments. With roots in extensive industry experience and its recent acquisition by Aptean, Logility’s solution is designed to streamline supply chain visibility and decision-making, even as its technical details regarding AI implementations remain broadly defined. |
| Lokad | Lokad is a supply chain optimization company that offers a cloud-hosted platform for quantitative decision-making in supply chains. It employs a proprietary domain-specific language called Envision, which enables supply chain experts to build and execute probabilistic forecasting and optimization models using methods such as automatic differentiation and stochastic gradient descent. The platform processes raw transactional data through an automated extraction pipeline and operates on a distributed, event-sourced, multi-tenant architecture, ensuring scalability, reproducibility, and secure collaboration with partners while addressing inventory management, demand forecasting, and pricing challenges through advanced statistical techniques. |
| Manhattan Associates | Manhattan Associates is a long-established software vendor that designs and delivers integrated supply chain and omnichannel commerce solutions. The company evolved from developing warehouse management systems to offering comprehensive applications for warehouse operations, transportation, order fulfillment, and inventory management. Its platform is constructed on a cloud-native, microservices-based architecture that uses containerization and agile orchestration for continuous deployment and flexible integration with both legacy systems and modern technologies. Additionally, the firm provides versatile deployment models—including on-premises, private cloud, and SaaS—while also incorporating AI-related enhancements, though the technical specifics of these machine learning components remain limited in public documentation. |
| Marradata.ai | Marradata.ai delivers data science solutions by converting raw business data into actionable insights through established data ingestion pipelines, predictive modeling, and machine learning techniques; the company supports supply chain optimization and operational decision-making by integrating data engineering processes, real-time dashboards, and customized reporting within a scalable SaaS framework. |
| Microsoft | Microsoft is a multinational technology company that designs, develops, licenses, and supports a wide range of software, hardware, and cloud-based services for both enterprise and consumer markets. Leveraging its Azure cloud platform, Microsoft delivers integrated solutions like Dynamics 365 Supply Chain Management, a modular ERP system that provides real‑time operational insights and process automation for supply chain, manufacturing, and financial management. The company employs established technology frameworks such as .NET and SQL Server, coupled with continuous delivery and customizable integration tools, to build resilient infrastructures that enable efficient data management, seamless interoperability with productivity applications, and scalable support for evolving business processes. |
| MJC² | MJC² is a UK‑based software editor that develops integrated decision‑support systems for planning and scheduling complex operations in logistics, manufacturing, supply chain, and workforce management. The company employs real‑time optimization techniques rooted in deterministic methods—including mixed‑integer programming and heuristic algorithms—to address multifaceted constraints in distribution routing, production scheduling, and workforce allocation. Its modular platforms are engineered to interface seamlessly with external systems such as ERP, SCADA, and telematics, thereby enabling dynamic rescheduling and just‑in‑time processing in challenging operational environments. Founded in 1990, MJC² focuses on research‑driven algorithm development to systematically tackle intricate planning challenges while ensuring precise constraint management and operational efficiency. |
| Netstock | Netstock is a cloud‐based SaaS provider that offers inventory planning and supply chain optimization solutions for small-to-medium-sized enterprises by integrating directly with ERP systems, automating data aggregation, and employing statistical forecasting alongside machine learning techniques to categorize inventory, predict demand, and generate real-time replenishment orders. Its modular platform supports coordinated sales and operations planning, streamlines order generation based on data-driven insights, and maintains seamless ERP connectivity to reduce stock-outs and excess inventory while facilitating collaborative decision-making across diverse business functions. |
| NextBillion.ai | NextBillion.ai is an API-first platform specializing in location technology for logistics and mapping that provides an integrated suite of services including route planning, distance matrix calculations, custom mapping, and dispatch management. It processes detailed input data such as vehicles, jobs, and locations by applying classical optimization and heuristic methods—with selective machine learning adjustments—to solve complex vehicle routing problems under constraints like time windows, vehicle capacity, and driver skill sets. The platform further supports flexible deployment models ranging from multi‑tenant cloud to private cloud and on‑premise configurations, enabling seamless integration with existing ERP and fleet management systems, and addressing the diverse operational challenges of modern supply chains. |
| nuVizz | nuVizz is a cloud-hosted SaaS provider that manages last‑mile delivery and transportation orchestration for industries including retail, healthcare, automotive, and furniture. The platform consolidates logistics operations by integrating real‑time tracking with AI and machine learning–driven dynamic route optimization that adjusts delivery paths based on live traffic, weather, and historical data. Its modular design supports specialized capabilities such as cross‑dock management, territory planning, and automated anomaly detection, while seamless integration with enterprise systems ensures synchronized, end‑to‑end visibility across the full delivery lifecycle. |
| o9 Solutions | o9 Solutions is a software company that develops a cloud-native enterprise platform for integrated planning and decision-making across supply chain, finance, and operations. The platform consolidates structured and unstructured data—sourced from spreadsheets, IoT devices, CRMs, and other systems—into a digital twin through a graph-based Enterprise Knowledge Graph. It applies statistical forecasting, machine learning, and scenario analysis to deliver real-time insights and prescriptive recommendations, while leveraging modern cloud infrastructures such as Microsoft Azure and big data processing frameworks for scalable, continuous integration and analysis. |
| Omniful | Omniful is a cloud‑native B2B SaaS platform that integrates order, warehouse, transportation, and point‑of‑sale management to support supply chain and omnichannel e‑commerce operations. The system combines established rule‑based processes with machine learning techniques for demand forecasting and route optimization, utilizing an API‑first architecture to interoperate with existing ERP, logistics, and retail systems. Built on modern technologies including Golang for backend services and React.js for responsive interfaces—with deployment typically achieved in 2–4 weeks under a subscription model—its founding history and acquisition structure reflect an evolving narrative influenced by initial founder investments and subsequent strategic support from a major technology investment firm. |
| OMP | OMP is a global provider of digital supply chain planning solutions that integrates demand forecasting, supply planning, production scheduling, inventory management, and distribution decisions into a unified platform. Founded in 1985, the company employs optimization methods such as linear and mixed integer programming, meta-heuristics, and simulation techniques alongside machine learning tools with explainable AI features to generate actionable insights from both historical and real-time data. Its solution is integrated with ERP systems like SAP to maintain accurate, synchronized data and is deployed via a cloud-based infrastructure on Microsoft Azure to support scalable, near real-time scenario analyses across a variety of industries. |
| OnePint.ai | OnePint.ai is an AI-driven inventory management solution established in 2025 that consolidates fragmented stock data into a single operational view through a suite of interlocking modules. The platform offers OneTruth for real-time inventory consolidation, Pint Control Center for simulation-based decision-making using autonomous AI agents, and Pint Planning for demand forecasting driven by real-time signals and probabilistic models. It is delivered as a cloud-hosted SaaS application designed for rapid deployment and seamless integration with ERP, WMS, and eCommerce systems, employing modern microservices-based infrastructure to optimize inventory accuracy and operational efficiency. |
| OPTANO | OPTANO is a German software company founded in 2009 that applies mathematical optimization and operations research techniques to address complex decision-making challenges in sectors such as automotive, logistics, production, and supply chain management. Its enterprise platform delivers interactive dashboards, scenario planning, and prescriptive analytics via a user‐friendly web interface, while its free, open‐source .NET Modeling API enables developers to build and solve optimization models using various commercial and open-source solvers. An accompanying Algorithm Tuner refines model parameters through metaheuristic methods, and its recent acquisition by Kearney has integrated these technical capabilities into a broader consulting framework focused on operational efficiency and decision support. |
| Optessa | Optessa is a Canadian company that develops advanced planning and scheduling solutions for complex production environments by employing patented “Fast Optimization” algorithms and deterministic operations research techniques. Its software integrates seamlessly with enterprise systems such as ERP and MES to generate optimized machine-level sequencing and scheduling, offering both on-premise and cloud deployment options. Designed to manage diverse production constraints and enable real-time schedule re-optimization during disruptions, the solution is used in industries like automotive manufacturing to improve resource utilization and adherence to production rules, all through user-configurable interfaces that simplify complex decision-making. |
| Optilogic | Optilogic is a technology company that develops cloud‑native, SaaS‑based supply chain network design solutions by integrating advanced mathematical optimization, dynamic simulation, and risk analysis techniques into its Cosmic Frog platform. Founded in 2005 and later augmented by the acquisition of INSIGHT Software in 2024, the company combines legacy expertise with modern scalability to evaluate complex supply chain scenarios — including transportation routing, inventory dynamics, and production policies — while its Leapfrog AI module converts natural language inputs into precise SQL queries and simulation commands, thereby facilitating data‐driven decisions and seamless integration with existing client systems. |
| Optilon | Optilon is an independent supply chain consulting firm founded in 2005 by engineers in the Nordics, with offices across Sweden, Denmark, Finland, and Lithuania. The firm does not develop proprietary software but instead assesses clients’ supply chain needs and tailors an ecosystem of best-in-class digital solutions—such as digital twin simulations for planning, predictive analytics for order monitoring, and machine learning modules for data correction—sourced from trusted external providers. By conducting detailed supply chain evaluations and employing a phased implementation strategy, Optilon integrates advanced tools and process optimization techniques to enhance operational transparency and efficiency in a methodical and evidence-based manner. |
| OptimiX Software | OptimiX Software is a French-based SaaS publisher founded in 2011 that provides retailers with data-driven solutions for pricing analytics and supply chain optimization. Its platform features two main products—Optimix XPA, which gathers and processes competitive pricing data via web scraping, in-store surveys, and automated product matching to simulate pricing strategies, and Optimix XFR, which refines historical sales data to forecast demand and generate order proposals. By integrating diverse data streams from web sources, retail environments, and enterprise systems, the solution employs a blend of traditional statistical methods and machine learning models such as linear regression and LightGBM to deliver real-time insights for dynamic decision-making in pricing and inventory management. |
| Oracle | Oracle is a multinational technology corporation that develops and delivers comprehensive enterprise solutions including cloud applications and on‑premise software. Its Oracle Fusion Cloud SCM solution integrates complex supply chain functions such as demand forecasting, production scheduling, backlog management, and sales and operations planning into a unified platform. Built on a service‑oriented architecture that leverages Fusion Middleware along with Oracle Cloud Infrastructure for scalability and security, the solution employs a unified data model and predefined APIs to facilitate cross‑functional integration and real‑time visibility. Oracle’s approach incorporates rule‑driven processes enhanced with predictive analytics and selective AI components, acknowledging that practical outcomes should be critically evaluated. |
| Orkestra Supply Chain Solutions | Orkestra Supply Chain Solutions develops a digital platform that centralizes global supply chain operations by aggregating data from disparate sources—including ERP, TMS, WMS, spreadsheets, and various logistical portals—into a unified, real‑time interface. The system is organized into modular components covering order and shipment management, data integration, supply chain visibility, analytics, and collaboration. Deployed on a cloud-native Microsoft Azure infrastructure, the platform is engineered to replace fragmented legacy processes with automated workflows and integrated dashboards, while reporting claims of operational cost and time savings and predictive analytics that have not been independently verified. |
| ORTEC | ORTEC designs and deploys optimization and analytics software that addresses complex NP‐hard challenges in logistics, supply chain, and workforce scheduling through advanced mathematical modeling, a mix of exact and heuristic algorithms, and seamless integration with enterprise systems such as SAP ERP. In parallel, its finance division provides tools for performance measurement, risk attribution, and climate scenario analysis by combining deterministic frameworks with stochastic simulations, all delivered via scalable SaaS platforms and modern web interfaces to support real-time, data‐driven decision-making. |
| Pando.ai | Pando.ai provides an AI-powered, no-code unified fulfillment platform that automates freight management by integrating modules for procurement, transportation, and financial reconciliation into one system. The platform consolidates data from ERP and TMS systems through pre-built connectors into a centralized logistics knowledge graph and employs proprietary AI agents to execute tasks such as RFQ generation, bid analysis, dynamic route planning, capacity optimization, load consolidation, invoice matching, and payment processing across domestic and international operations. |
| ParkourSC | ParkourSC is a software company that transforms supply chain management through a cloud‑native platform which creates detailed digital twins by aggregating real‑time sensor, operational, and external data. The system continuously monitors asset conditions, inventory levels, and process metrics, employing an event‑driven automation framework that combines rule‑based logic with AI/ML techniques to forecast and mitigate disruptions. Its approach integrates seamlessly with existing ERP systems and facilitates coordinated operations among suppliers, manufacturers, and logistics partners via customizable, low‑code interfaces. |
| PartnerLinQ | PartnerLinQ is a digital platform engineered to unify supply chain connectivity by integrating a diverse range of enterprise systems through a modular, cloud-native architecture. The solution supports multiple communication protocols—such as EDI, API, XML, and JSON—and offers pre-configured business rule engines, plug-and-play adapters, and a unified API management layer to bridge legacy infrastructures with modern IT environments. Available in both SaaS and on-premise forms, the platform provides near-real-time visibility via dashboards and streamlined operational workflows, while also purporting to incorporate AI-driven decision intelligence for tasks like demand forecasting and inventory optimization. Despite extensive vendor documentation on its composability and integration features, independent technical validation and detailed operational metrics remain limited. |
| Perfect Planner | Perfect Planner is a cloud‐based material planning and replenishment platform that integrates data from existing MRP systems, warehouse management systems, and spreadsheets to automatically generate prioritized daily task lists for material planners and buyers. It employs a proprietary Intelliplanning® Logic Engine that applies over 2,000 rule‐based algorithms per SKU to transform raw planning data into actionable insights, reducing manual administrative workloads. The platform further provides real-time dashboards and key performance indicators to enhance supply chain visibility while aligning with established methodologies such as Lean, Six Sigma, TQM, and Agile to support accurate and efficient decision-making in supply chain operations. |
| Pigment | Pigment is a cloud-native enterprise planning and performance management platform that consolidates data from finance, operations, sales, and supply chain into a single, real-time view for budgeting, forecasting, and scenario analysis. The system integrates data automatically through a modern tech stack and a layered Test & Deploy framework that allows safe updates of complex models, while specialized AI agents analyze trends, detect anomalies, and optimize planning processes to support informed, collaborative decision-making without replacing human oversight. |
| PlanetTogether | PlanetTogether is a software company offering advanced planning and scheduling solutions for manufacturers by integrating with ERP, MES, and SCM systems to deliver real-time production scheduling, capacity optimization, and supply chain coordination. Its platform employs constraint-based optimization algorithms to handle complex production challenges—including material, machine, and labor limitations as well as sequence-dependent changeovers—and incorporates a machine learning module, Copilot, to analyze operational data for demand forecasting, predictive maintenance, and scenario simulation, thereby streamlining scheduling processes with a design that necessitates independent technical validation of its AI-driven claims. |
| Plan Optimus | Plan Optimus develops integrated supply chain planning software for the manufacturing, retail, and distribution sectors. Its SaaS platform unites demand forecasting, integrated business planning, sales and operations planning, and logistics optimization by combining established statistical techniques, AI/ML methods, and mathematical optimization solvers. The system integrates real-time data from disparate sources and offers cloud scalability, secure ERP and Excel connectivity, and scenario simulation to coordinate production, procurement, and financial operations across complex supply chains. |
| Pluto7 | Pluto7 develops cloud-based software solutions for supply chain optimization by integrating internal ERP data with external signals such as weather, economic trends, and social indicators. The company employs robust ETL processes to standardize and blend disparate data sets into canonical views that serve as the foundation for advanced machine learning and artificial intelligence models. Utilizing Google Cloud technologies like BigQuery and Vertex AI, Pluto7’s platform delivers real-time insights via digital replicas of supply chains, enabling demand sensing, forecasting, and inventory planning through streamlined MLOps practices. |
| ProvisionAi | ProvisionAi develops supply chain optimization software that improves logistics operations by combining traditional mathematical techniques—such as linear programming and operations research—with iterative reinforcement learning to generate efficient truck load configurations and balanced transportation schedules. Its AutoO2 solution calculates optimal product arrangements that adhere to constraints like axle weight limits and stacking rules, while LevelLoad refines shipment planning and carrier selection by smoothing demand over time. Established in the early 1990s and evolved through strategic mergers, the company designs its systems to integrate with existing ERP and warehouse management infrastructures, aiming to improve load efficiency, reduce product damage and freight cost, and achieve operational improvements without relying solely on state-of-the-art deep learning models. |
| PTC | Founded in 1985, PTC is an American software and services company that develops industrial solutions for computer‐aided design, product lifecycle management, Internet of Things connectivity, and augmented reality while also specializing in service parts management through its 2012 acquisition of Servigistics; the company employs algorithmic multi‐echelon inventory optimization, advanced statistical forecasting, digital twin simulations, and machine learning techniques within its cloud‐based SaaS deployments to streamline spare parts planning and support the operational complexities of industries such as aerospace, defense, automotive, and industrial equipment. |
| Pyplan | Pyplan is a planning and data analytics platform that integrates key business functions—sales, operations, HR, and finance—into a unified low-code environment using a node-based graphical interface to construct Python-based calculation workflows; it connects to spreadsheets, databases, and APIs and leverages established Python libraries for data processing and visualization, while deploying containerized microservices via Kubernetes across cloud and on-premises infrastructures and integrating external machine learning frameworks for demand forecasting, anomaly detection, and automated reporting in adherence with industry-standard practices. |
| QAD Inc. | QAD Inc. provides cloud‑based ERP and supply chain management solutions specifically designed for adaptive manufacturing enterprises. The company’s layered enterprise platform integrates foundational infrastructure services with a core model of reusable business components, enabling the automation of manufacturing processes through standardized best practices and tailored application extensions. It incorporates advanced machine learning techniques and AI modules—including a conversational digital assistant—to analyze process data, detect anomalies, and drive operational insights. Additionally, QAD employs a structured onboarding methodology to manage complex ERP implementations, while also integrating capabilities acquired from complementary technologies to enhance process mining and connected workforce analytics. |
| RELEX Solutions | RELEX Solutions provides a unified software platform for supply chain and retail planning that integrates demand forecasting, inventory management, automatic replenishment, production scheduling, and distribution planning. The platform harnesses advanced data processing—including in-memory computing and in-database analytics—combined with machine learning, mathematical optimization, and rule-based adjustments to create a real-time digital twin of client operations. Its cloud-native, microservices-based architecture supports rapid, configurable rollouts designed to reduce waste, minimize stockouts, and improve operational efficiency through precise, data-driven decision making. |
| River Logic | River Logic is a privately held software company based in Dallas, Texas that delivers a prescriptive analytics solution known as the Digital Planning Twin—a platform that digitally replicates a company’s entire value chain, including sourcing, production, logistics, financials, and sustainability metrics, to simulate and optimize complex, cross-functional trade-offs. The solution leverages advanced mathematical optimization techniques such as linear and mixed integer programming by integrating the Gurobi Optimizer, and is built on a modern technical stack featuring JavaScript, Node.js, Docker, and other contemporary tools. Offered as a cloud-based SaaS with a code-free, drag-and-drop interface, it facilitates rapid what-if scenario analysis and decision support through a structured, phased deployment model that encompasses discovery, design, setup, and model validation. Additionally, while it incorporates elements of artificial intelligence and machine learning to streamline routine tasks, its core functionality remains grounded in established operations research methods to provide actionable, simulation-driven insights. |
| Sabre Corporation | Sabre Corporation is a travel technology provider with decades of experience in airline operations management that develops integrated solutions using established optimization and constraint modeling techniques; its products, such as Fleet Manager, combine booking forecasts, revenue management data, and real‑time operational inputs to simulate various fleet assignment scenarios while addressing maintenance, capacity, and scheduling constraints within a modern, cloud‑native, API‑driven architecture that supports both immediate operational adjustments and long‑term strategic planning. |
| Salesforce | Salesforce is a cloud-based enterprise platform that began as the first SaaS CRM in 1999 and has grown into an integrated ecosystem combining sales, service, marketing, and commerce. Its metadata-driven, multi-tenant architecture—recently evolved through Hyperforce—supports scalable public cloud deployments with flexible data residency. The platform integrates low-code development tools, extensive APIs, and embedded AI capabilities (such as Einstein and Agentforce) alongside middleware solutions from acquisitions like MuleSoft and Data Cloud, thereby unifying customer data and streamlining operational workflows through established industry practices. |
| SAP | SAP is a multinational enterprise software company that develops integrated business solutions for managing supply chain operations, enterprise resource planning, and data analytics. The company harnesses cloud‐based architectures and in‑memory computing via SAP HANA alongside statistical models and modular machine learning frameworks to create configurable systems that support demand forecasting, supply planning, inventory optimization, and sales‑and‑operations planning, thereby unifying diverse operational data and enabling real‑time simulation and scenario analysis in dynamic market environments. |
| SCM Globe | SCM Globe is a cloud‐based supply chain simulation platform that enables users to design, simulate, and analyze supply chain networks by configuring key entities such as products, facilities, vehicles, and routes. Using a map‐based drag and drop interface built on Google Maps and a discrete event simulation engine that updates operations on an hourly basis, the platform generates comprehensive reports including profit & loss outcomes and key performance indicators. The system supports academic, professional, and enterprise use cases while employing necessary approximations and averaging techniques that require careful interpretation of simulation outputs. |
| Siemens Digital Industries Software | Siemens Digital Industries Software develops industrial application platforms that support the entire product lifecycle—from computer‐aided design and simulation to integrated product data management and manufacturing optimization. The software combines in-house R&D with strategic acquisitions to merge traditional CAD, CAE, and PLM capabilities with digital twin technology and AI/ML-driven adaptive interfaces. It enables simulation, real-time monitoring, and predictive maintenance while offering flexible on-premises, cloud, and hybrid deployment models, ensuring interoperability across diverse engineering and production environments. |
| Sigma Computing | Sigma Computing is a cloud-native analytics and business intelligence platform that enables business users to explore and analyze live data stored in major cloud data warehouses using a familiar spreadsheet-like interface; it directly connects to systems such as Snowflake, Google BigQuery, and Amazon Redshift to execute real-time queries while keeping data securely in place, supports collaborative editing and version control, and incorporates AI and machine learning functionality by leveraging existing large language models from cloud providers—all integrated within a modern, multi-cloud SaaS architecture designed for performance, security, and scalability. |
| Silvon Software | Silvon Software, Inc., founded in 1987, develops the Stratum business intelligence platform designed for manufacturers, distributors, and retailers by centralizing and analyzing operational data from both legacy and modern ERP systems; it delivers predefined reports, KPIs, dashboards, and alerts via standardized connectors and a centralized data hub, and employs a phased, in-house implementation approach using enterprise-grade tools such as Microsoft SQL Server, SSIS, and SSRS to support consistent performance management. |
| Simcel | Simcel is a cloud-based integrated business planning platform that employs digital twin simulation and data integration to provide real-time assessments of operational and financial scenarios. Launched in 2023 and leveraging decades of supply chain management experience from its parent consultancy CEL, the platform aggregates transactional data from systems such as ERP, WMS, and POS to simulate and evaluate “what-if” scenarios across demand forecasting, supply chain logistics, finance, and sustainability metrics. Its technology stack—including Angular for the frontend, NodeJS (NestJS) with Typescript, Python, and cloud-native tools like Docker, Kubernetes, and AWS—supports rapid simulation of complex business environments and key performance indicator analysis without offering extensive public technical documentation on its AI or machine learning methodologies. |
| SkyPlanner | SkyPlanner provides a cloud‐based Advanced Planning and Scheduling solution that automates production planning and manufacturing scheduling by integrating real‐time shop floor data from ERP and MES systems via advanced REST APIs. The system employs its in‐house Arcturus AI engine to analyze constraints such as machine capacity, material availability, labor shifts, and interdependencies between production stages, dynamically adjusting production schedules through an interactive GANTT timeline interface that displays job statuses, priorities, and facilitates task splitting and mobile confirmations, all while allowing human oversight for necessary adjustments. |
| SKU Science | SKU Science is a cloud-hosted SaaS platform that delivers demand and sales forecasting for supply chain and operations management by analyzing historical sales data through an ensemble of 644 preconfigured statistical models. The solution generates forecasts at multiple aggregation levels-supporting Sales & Operations Planning, master scheduling, and product lifecycle management-while offering interactive dashboards that display demand curves, forecast accuracy, and key performance indicators, and permit manual adjustments in real time. Deployed on AWS with standard security certifications, it enables rapid implementation and secure operation, and it also provides consulting services to incorporate additional variables into custom forecasting models. |
| Slimstock | Slimstock is a privately held software vendor founded in 1993 that develops supply chain planning and inventory optimization solutions through its Slim4 platform. It delivers functionalities including demand forecasting, replenishment planning, and modular sales and operations planning and execution with real-time analytics and scenario simulation. The platform supports both cloud-based and on-premise deployments and integrates with various ERP systems using established enterprise technologies such as Microsoft SQL and Power BI. Although marketed with AI-powered features, its technical details remain limited, suggesting that its advanced data analysis primarily relies on enhanced statistical methods within an agile development framework characterized by frequent updates. |
| Solvoyo | Solvoyo provides an end-to-end supply chain planning platform that integrates strategic, tactical, and operational decision processes—covering demand forecasting, inventory optimization, production planning, replenishment, transportation, pricing, and vendor collaboration. The platform employs advanced mathematical optimization techniques like Mixed-Integer Linear Programming with established solvers, complemented by AI and machine learning models to support predictive and prescriptive analytics. It is built on a unified data model that facilitates integration via multiple protocols and is delivered as a cloud-native SaaS solution designed for scalable, modular deployments in complex supply chain environments. |
| Sophus Technology | Sophus Technology provides an integrated platform for supply chain network design and optimization that consolidates production planning, inventory management, demand forecasting, and network design under one system. The solution applies advanced mathematical optimization algorithms and established AI techniques, such as gradient boosted multivariate regression, to automate data cleansing, integration, and scenario analysis. It supports flexible deployment options—including cloud-native environments and on-premise configurations—to address both operational efficiency and regulatory compliance, while offering an intuitive, no-code interface designed for business users. |
| StockIQ Technologies | StockIQ Technologies develops an end‐to‐end supply chain planning suite that encompasses demand forecasting, inventory and replenishment management, supplier performance tracking, promotion planning, and Sales, Inventory & Operations Planning (SIOP). Founded in 2015 by experienced industry professionals, the company integrates historical sales data with real‐time inputs from ERP systems and IoT devices to generate actionable inventory and operational insights. Its platform is deployable on both cloud-based and on-premise infrastructures via a structured 28-day implementation process, and while it claims to leverage advanced algorithmic and AI/ML techniques, the specific technical details behind these approaches remain publicly limited. |
| Streamline | Streamline develops an integrated sales and operations planning solution that aggregates and processes data from diverse sources—such as ERP systems, spreadsheets, and databases—to enable synchronized planning across sales, operations, and finance. Its cloud-based platform employs standardized data preparation techniques and a machine learning engine, which draws on established methodologies akin to the Group Method of Data Handling, to deliver demand forecasts, optimize inventory, and facilitate resource allocation. The solution features interactive, real-time dashboards and supports seamless API/ODBC integrations, thereby enabling data-driven scenario planning and efficient supply chain management without overstating technical innovations. |
| SupplyBrain | SupplyBrain is a digital startup that develops a cloud-based supply chain management platform using data-driven methods and real-time digital twin simulations to evaluate and optimize warehouse operations. The platform processes historical and live inventory data to simulate the flow of goods, identify bottlenecks, optimize product slotting, and improve personnel planning. It further integrates sensor data and machine logs within a predictive maintenance framework through anomaly detection and multiple AI models to forecast equipment needs and demand, thereby informing inventory reviews and replenishment decisions. Built on modern technologies including Python, Kotlin, and cloud infrastructures with containerization and microservices architecture, the solution is designed to integrate with existing ERP systems while functioning within an established logistics ecosystem. |
| Supply Chain dApp | Supply Chain dApp develops a decentralized platform that leverages Ethereum blockchain technology and smart contracts to create immutable, tamper‐proof records for each stage of a product’s lifecycle. The system employs standard development tools such as Truffle, Ganache, React.js, and Web3.js to digitally capture and verify supply chain events—from manufacturing to delivery—while purporting to integrate IoT sensor data for real-time monitoring. This approach aims to replace manual, paper-based processes with automated, cryptographically secured logs that enhance traceability, security, and auditability across complex supply chain operations. |
| SymphonyAI | SymphonyAI is an enterprise AI SaaS company founded in 2017 that develops industry-specific solutions using its proprietary Eureka AI platform, which combines advanced data processing—including topological data analysis—with predictive, generative, and agentic models. The company addresses diverse markets such as retail/CPG, financial services, industrial, enterprise IT, media, and trading/investing by integrating structured and unstructured data via a layered architecture, delivering applications for tasks like demand forecasting, real‑time monitoring, financial crime detection, and manufacturing optimization, while supporting multiple deployment environments. |
| Syncron | Syncron is a global software company that delivers a cloud-based, modular SaaS platform for aftermarket service lifecycle management by combining inventory optimization, dynamic pricing, demand forecasting, and service fulfillment into an integrated system that connects with ERP, MES, and IoT architectures; established in 1990 and expanded through the 2021 acquisition of Mize, it employs conventional data analytics and machine learning techniques to streamline operations, reduce downtime, and manage costs for manufacturers worldwide. |
| Syren | Syren provides cloud-based solutions for supply chain optimization and data engineering by integrating diverse enterprise data sources into unified, real-time dashboards and control towers that monitor operations from procurement through delivery. The company’s platform automates data quality management through rule-based cleansing and configurable governance while applying predictive analytics and machine learning methods to manage order fulfillment, dynamic inventory, and asset tracking. Deployed via a SaaS model that leverages Infrastructure as Code and modern cloud ecosystems, its suite delivers insights and operational monitoring—including IoT-enabled tracking and sustainability metrics—designed to consolidate data streams and support scalable, secure supply chain performance. |
| The Owl Solutions | The Owl Solutions is a privately financed technology firm that develops a cloud‑based supply chain analytics platform. It aggregates data from disparate ERP and production systems into pre‑configured dashboards and scorecards that display real‑time insights into inventory levels, demand planning, supplier performance, and working capital management. The platform offers flexibility through hosted cloud deployment or seamless integration with existing corporate BI tools, thereby automating data collection and reporting processes in manufacturing supply chains. |
| thouSense | thouSense is an AI-powered SaaS platform that enables small and medium businesses to tackle demand forecasting and supply chain planning by processing historical sales data (uploaded via CSV) alongside configurable hierarchical inputs and external indicators such as weather and economic data; the system employs machine learning algorithms to dynamically generate short- and long-term forecasts, supports scheduled forecast runs with automated email alerts and customizable report exports within an intuitive cloud-based interface, and while it emphasizes advanced AI capabilities, detailed technical documentation on its underlying models and validation processes remains limited. |
| ThroughPut Inc. | ThroughPut Inc. is a provider of a SaaS-based supply chain decision intelligence platform that integrates operational data from ERP, MES, PLC, and other systems through pre-built connectors into a centralized analytics engine. The platform employs established continuous improvement practices—including Lean methodologies and the Theory of Constraints—combined with time-series forecasting and heuristic algorithms to identify bottlenecks, forecast demand, and optimize capacity and logistics planning. It supports flexible deployment options (cloud, on-premise, or hybrid) to integrate seamlessly with existing IT infrastructures while delivering actionable insights designed to improve operational efficiency and resource allocation. |
| TigerGraph | TigerGraph is a privately held software company that delivers a real-time graph analytics platform built on a proprietary native parallel graph architecture. The system processes massive, connected datasets using a dual-engine approach—with a custom Graph Storage Engine and Graph Processing Engine developed in C++—that leverages data locality and built-in parallelism for rapid, multi-hop queries. It utilizes a Turing-complete, SQL-like language (GSQL) to facilitate advanced analytics, in-database machine learning, and graph data science tasks across applications such as fraud detection, cybersecurity, and supply chain analysis. The platform is available both as a self-managed deployment and in cloud-native configurations, with design choices emphasizing efficient data compression and scalability that warrant independent validation. |
| ToolsGroup | ToolsGroup develops integrated software solutions for supply chain planning and demand analytics by employing probabilistic forecasting, multi-echelon inventory optimization, and machine learning techniques to manage demand variability and coordinate replenishment. Its platform is built on a modular, cloud-native architecture that interfaces seamlessly with ERP and legacy systems, and it has expanded its functionality through strategic acquisitions that introduced dynamic pricing and real-time inventory reallocation capabilities. The system combines advanced statistical models with rule-based automation and phased deployment strategies to support data‐driven decision making across complex supply chain networks while reducing manual planning efforts and maintaining consistent operational outcomes. |
| Transmetrics | Transmetrics develops a cloud-based SaaS platform that uses artificial intelligence and machine learning to support logistics and transport operations through data-driven decision support. The solution integrates with existing enterprise systems such as TMS and ERP by organizing its functionality into modules for forecasting, analytics, and optimization. It processes historical data together with external factors—such as weather, public holidays, and market conditions—using techniques like data cleansing, natural language processing, gradient boosting, and mixed-integer programming to generate predictive models for demand, supply, and operational adjustments. Built with a modern technology stack including Java, Python, and containerized deployments, the platform targets challenges in fleet utilization, cost efficiency, and industry-specific operations like trucking, container management, linehaul planning, and fleet maintenance, though the underlying performance claims are based on proprietary methods that benefit from independent validation. |
| Turvo | Turvo provides a cloud‑based transportation management platform that consolidates order management, real‑time shipment tracking, appointment scheduling, and inventory oversight into a single SaaS solution. Founded in 2014 and acquired by Lineage Logistics in 2022, the platform uses a modern cloud‑centric architecture with RESTful APIs and mobile applications to facilitate real‑time collaboration among shippers, brokers, carriers, and third‑party logistics providers while replacing manual processes with integrated, scalable digital workflows. |
| UCBOS | UCBOS is an enterprise software provider based in Atlanta, USA that offers a zero‐code transformation platform built on a metadata‐driven, schema‐free architecture; the platform integrates supply chain management, procurement, ERP functions, and AI/ML capabilities through configurable modules that enable rapid application composition, real‐time data orchestration, and semantic connectivity among legacy systems, IoT devices, and cloud applications while supporting both fully managed and self‐managed deployment models in public cloud environments. |
| UnitySCM | UnitySCM is a cloud-delivered supply chain management provider that consolidates data from enterprise systems like ERP, WMS, and TMS along with spreadsheets, emails, and other unstructured sources into a unified digital view; it normalizes and enriches this data in real time using rules-based processing supplemented by machine learning techniques for anomaly detection and workflow automation—including dispute resolution for shipment fees—and integrates with legacy systems via a modular, configurable architecture built on an AWS-centric technology stack. |
| Vekia | Vekia is a French software vendor that develops a SaaS-based supply chain management solution using probabilistic artificial intelligence and machine learning to forecast demand through multiple simulated scenarios, generate automated order proposals, and provide real-time inventory and logistics monitoring; it integrates with ERP, WMS, and CRM systems using cloud infrastructure such as Microsoft Azure and a microservices architecture to support efficient stock optimization and shortage management. |
| Waymetry | Waymetry, founded in Lithuania in 2024, develops a cloud‑based software-as-a-service platform that automates pricing and contract management for road transport and logistics companies by integrating fixed cost parameters with real‑time market data to generate tender and spot‐rate calculations, track fleet capacity, and update margins; its suite of interconnected tools relies on rule‑based automation—with nominal AI claims—designed to streamline complex pricing workflows without detailed public disclosures of its underlying technical methods. |
