If you’re searching for the best AI-powered supply chain analytics software in 2025, you’re likely trying to forecast demand more accurately, prevent stockouts, cut excess inventory, and avoid disruptions before they hit your bottom line.

Most companies today sit on massive amounts of supply chain data, yet only a fraction of it turns into real insight.

Orders get delayed, inventory piles up in the wrong locations, and teams spend hours firefighting because signals stay hidden inside scattered spreadsheets and disconnected systems.

AI supply chain analytics is no longer a nice upgrade. It is the clearest path to understanding where demand is heading, which suppliers pose risk, and how to keep operations stable in unpredictable markets.

That is why choosing the right platform matters.

In this guide, we compare the 10 leading AI supply chain analytics tools of 2025, outline their strengths, limitations, and ideal use cases, and explain why Upsolve stands out for visibility, forecasting accuracy, and fast time to value.

TL;DR: The 10 Best AI-Powered Supply Chain Analytics Software Overall

Here is a quick overview of the top supply chain analytics platforms in 2025, which we cover in detail later in the guide:

Best for Embedded Supply Chain Intelligence: Upsolve

Provides fast, intuitive dashboards and forecasting views that embed directly into your systems, ideal for teams that want clear visibility without heavy implementation.

Best for Enterprise End-to-End Planning: Blue Yonder

Strong demand planning, inventory optimisation, and logistics execution, though often complex and priced at the enterprise level.

Best for Digital Twin and Scenario Planning: o9 Solutions

Robust modelling and what-if simulation for global networks, but requires mature data and careful implementation.

Best for Rapid Decision Cycles: Kinaxis RapidResponse

Concurrent planning and control-tower views built for speed, with a learning curve for deeper features.

Best for SAP-Centric Enterprises: SAP IBP

Powerful planning suite tightly integrated with SAP ERP, though configuration and upkeep demand expertise.

Best for Cloud-Native Enterprise Planning: Oracle Supply Chain Planning Cloud

Predictive planning, constraint-based optimisation, and strong analytics for large organisations, with some UX trade-offs.

Best for Complex Order Ecosystems: IBM Supply Chain Intelligence Suite

Designed for visibility, orchestration, and predictive insights in high-volume order environments.

Best for Multi-Enterprise Visibility: Infor Nexus

Ideal for suppliers, carriers, and retailers who need shared visibility across regions, though adoption improves as more partners join the network.

Best for Mid-Market Planning: John Galt Atlas

Reliable forecasting and inventory planning with faster implementation compared to heavyweight suites.

Best for Multi-Echelon Inventory Optimisation: ToolsGroup SO99+

Advanced inventory optimisation and demand sensing for distributors and retailers, with deeper functionality than many general-purpose tools.

Quick Comparison Table: Best AI Supply Chain Analytics Tools in 2025

Not all supply chain analytics platforms solve the same problems. Some excel at end-to-end planning, others specialise in digital twin simulation or multi-enterprise visibility.

A few are ideal for mid-market teams, while others are built strictly for large enterprise networks.

Here is the clear side-by-side breakdown so you can see which platform fits which use case.

What is AI-powered Supply Chain Analytics?

AI supply chain analytics refers to systems that use machine learning, statistical models, and automation to analyze supply chain data and produce forecasts, risk signals, and recommendations.

Typical flows are:

1. Data ingestion: ERP, WMS, TMS, EDI, IoT telematics, and spreadsheets feed into a central layer.
   
   

2. Feature engineering and models: The system builds demand signals, seasonality, promotion impacts, and supplier lead time distributions.
   
   

3. Forecasting and optimization: ML models generate short- and mid-term forecasts. Optimization engines propose inventory, allocation, and reorder policies.
   
   

4. Simulation and scenario planning: Digital twins or scenario planners calculate impacts of supply shocks, tariff changes, or site outages.
   
   

5. Action and orchestration: The platform recommends or triggers orders, alerts planners, and integrates with execution systems.

Why 2025 is different. Several capabilities matured that make AI practical for mainstream adoption: improved model explainability, wider availability of prebuilt connectors, and control tower frameworks that unify network-wide telemetry. Vendors advertise explainable AI and digital twin capabilities as standard parts of their stacks. 

Benefits of AI Supply Chain Analytics in 2025

Here are the key benefits of AI supply chain analytics in 2025 – 

• Improved forecast accuracy. Modern models combine causal signals, promotions, and channel data to narrow forecast error. That reduces both excess inventory and stock-outs. Vendor case studies and user reviews report measurable improvements after deployment.
  
  

• Real-time visibility. Control tower and visibility modules show in-transit shipments, order statuses, and potential delays on a single pane. This enables earlier interventions.
  
  

• Multi-echelon inventory optimization. Platforms with multi-tier optimization compute optimal safety stock across factories, DCs, and stores to meet service targets at minimum cost. ToolsGroup SO99+ and similar vendors highlight this capability.
  
  

• Faster decision cycles. Scenario planning and automated recommendations shorten the time from signal detection to corrective action. This matters during disruptions and promotional peaks.
  
  

• Supplier risk and ESG visibility. Several vendors now include risk scoring and sustainability modules, which support compliance and long-term resilience. Infor Nexus provides supplier and sustainability functionality focused on ESG.
  
  

• Lower operational cost. Automating routine planning tasks reduces headcount pressure on planners and reduces errors from spreadsheets. Multiple vendors and customers report improved planner throughput.

Key Features to Look for in AI-Powered Supply Chain Analytics Softwares

When evaluating vendors, prioritize the features that align with your top pain points.

• Demand forecasting with causal variables and promotion handling.
  
  

• Multi-echelon inventory optimization and service level targeting.
  
  

• Real-time visibility and control tower views for in-transit and supplier statuses.
  
  

• Digital twin / scenario simulation to test shocks and mitigations.
  
  

• Supplier risk scoring and multi-tier alerts.
  
  

• Integrations with ERP, WMS, TMS, marketplaces, and EDI.
  
  

• Explainable AI so planners trust the recommendations.
  
  

• Embedded analytics or dashboards for role-based KPIs.
  
  

• Flexible deployment: cloud SaaS or hybrid, depending on data residency needs.
  
  

• Security and compliance: SOC2, ISO, GDPR as needed for your region.

All vendor claims should be validated with a pilot. Look for vendors that supply prebuilt connectors to your core systems; that reduces implementation time.

How Did We Choose the Best AI Supply Chain Analytics Software?

To identify the strongest AI-powered supply chain analytics platforms of 2025, we evaluated each vendor using a consistent set of criteria:

• Overall reliability and system performance during high-volume planning cycles.
  
  

• Breadth of coverage across demand planning, inventory optimisation, logistics, and supplier visibility.
  
  

• How quickly a business can implement the platform without requiring months of heavy IT work.
  
  

• Forecast accuracy, prediction quality, and the strength of optimisation models reported by customers.
  
  

• Clarity of pricing and subscription structure, especially for enterprise deployments.
  
  

• Security certifications and compliance with standards such as SOC 2, ISO, and GDPR.
  
  

• Integration readiness, including connectors for ERP, WMS, TMS, EDI, and partner systems.
  
  

• Reputation and independent user reviews across G2, Capterra, Gartner Peer Insights, and other trusted sources.
  
  

• Quality of vendor onboarding, customer support, and long-term account management.
  
  

• Availability of advanced capabilities such as digital twins, scenario planning, control tower views, AI-based alerts, and custom dashboards.

10 Best AI-Powered Supply Chain Analytics Software

Here are our top 10 AI-powered supply chain analytics softwares that you must try in 2025 – 

1. Upsolve AI

Upsolve AI is an embedded analytics and BI platform designed to provide role-specific dashboards and quick, embeddable analytics components for product and operations teams. 

Upsolve AI aims to be lightweight, fast to deploy, and straightforward to embed into a customer product or internal portal. 

This AI supply chain analytics software focuses on delivering actionable dashboards and predictive insights rather than being a full-blown ERP or planning engine.

Key features

• Prebuilt, embeddable dashboards for inventory and demand forecasting.
  
  

• Role-based views and React component embeds for product integration.
  
  

• Fast dashboard building with low-code UI and templates.
  
  

• Use cases focused on visibility, risk alerts, and simple forecasts.

Pros

• Quick to deploy and embed in external products.
  
  

• Suited to teams that need clear dashboards without heavy implementation cycles.

• Transparent documentation and customer case studies for embedded use.

Cons

• Not a full planning suite. Does not replace ERP or deep multi-echelon optimization engines.
  
  

• Better suited for visibility and analytics than for complex scenario-based planning.

Pricing & Plans

Growth – $1,000+ / month

Basic embedded analytics to get started:

• 3+ dashboard templates
  
  

• 25+ tenants included
  
  

• Dashboard custom styling
  
  

• iFrame & React component embedding
  
  

• CSV & PDF export

Professional – $2,000+ / month

Adds more power and flexibility:

• All Growth plan features
  
  

• Unlimited embedded dashboard templates
  
  

• 25+ tenants
  
  

• AI-driven analytics for end-users
  
  

• Scheduled email reports
  
  

• End-user usage analytics
  
  

• Dedicated support & onboarding

Enterprise – Custom pricing

Full-scale deployment for advanced use cases:

• All Professional plan features
  
  

• Unlimited tenants
  
  

• Unlimited data-plane connections
  
  

• End-user facing AI analytics agent
  
  

• SAML SSO
  
  

• HIPAA support (coming soon)
  
  

• 24/7 dedicated support & onboarding

Best for
Product teams, startups, and mid-market companies that need to add role-based analytics to internal products or customer portals quickly.

2. Blue Yonder

Blue Yonder, a long-standing provider in retail and supply chain planning, positions itself as a complete planning and execution stack with heavy investments in AI and machine learning. 

The product portfolio spans demand planning, warehouse execution, transportation planning, and store fulfillment.

This AI supply chain analytics software emphasizes high-volume prediction workloads and operational execution.

Key features

• Demand and inventory optimization.
  
  

• Warehouse management and execution.
  
  

• Advanced transportation planning and yard management.
  
  

• Large-scale ML models and a common data cloud for real-time predictions.
  
  

Pros

• Broad functional coverage for retail and distribution.
  
  

• Strong execution modules for WMS and TMS integration.
  
  

• Significant enterprise footprints and customer references.
  
  

Cons

• Complex implementations and long lead times.
  
  

• Recent incidents have highlighted the need to verify operational resilience with third-party services. There are reports of cyber incidents affecting operations at major customers tied to the vendor ecosystem.

Pricing & Plans

Blue Yonder offers modular licensing and partners for pricing. Contact vendor for tailored quotes.

Best for
Large retailers, grocers, and distributors that need a single vendor for planning, warehouse execution, and transportation.

3. o9 Solutions

o9 markets the Digital Brain, a planning and decision platform that combines forecasting, planning, and a digital twin approach to end-to-end supply chain planning. 

The company has been recognized repeatedly in analyst research for supply chain planning. 

o9 focuses on scenario-based planning and complex network modeling for enterprises with global operations.

Key features

• Digital twin for scenario simulation.
  
  

• Integrated demand, supply, and revenue planning.
  
  

• Cross-functional collaboration workflows and KPI tracking.
  
  

• AI-driven forecasting and what-if analysis.

Pros

• Strong at aligning forecasting, supply planning, and financials.
  
  

• Robust simulation and scenario features for network-level decisions.

Cons

• Higher cost and longer deployments for large-scale rollouts.
  
  

• Requires strong internal data discipline for fastest outcomes.

Pricing and Plans

o9 uses enterprise pricing. Prospective buyers must request demos and custom quotes.

Best for
Global manufacturers and retailers that need to model multi-region supply networks and run frequent scenario simulations.

4. Kinaxis Maestro

Kinaxis built Maestro (formerly known as RapidResponse) for concurrent planning.

The platform emphasizes agility, scenario planning, and control tower functionality. Kinaxis also markets AI-enabled agents that can act on signals and assist planners. 

This AI supply chain analytics software is used by companies that need fast response cycles and tight integration between planning and execution.

Key features

• Concurrent planning and what-if simulation.
  
  

• Control tower views and alerting.
  
  

• AI assistants that automate parts of the planning workflow.
  
  

• Integrations to ERP and execution systems.

Pros

• Fast scenario response and collaborative planning.
  
  

• Good fit for environments where decision speed matters more than massive feature lists.

Cons

• Requires mature data inputs to reach full potential.
  
  

• Learning curve for advanced functionalities.

Pricing and Plans

No public per-seat price. Analyst and review estimates place annual licensing commonly in the $250k to $1M range for enterprise deployments depending on scope and modules, plus implementation fees.

Best for
Companies that need fast decision cycles across S&OP and prefers an agile, collaborative planning tool.

5. SAP Integrated Business Planning (IBP)

SAP IBP is the enterprise planning suite within the SAP stack.

It offers advanced forecasting, inventory optimization, and scenario planning. 

SAP IBP is a natural fit for enterprises already invested in SAP ERP who want tight integration and end-to-end planning capabilities. 

Key features

• Demand planning, inventory optimization, and supply planning modules.
  
  

• Excel-like planning views and data integration via SAP tools.
  
  

• Enterprise-scale features and deep configuration options.

Pros

• Tight integration with SAP ERP and a broad partner ecosystem.
  
  

• Strong analytics and reporting capabilities.

Cons

• Complexity and potentially slower performance in large models.
  
  

• Setup and change management require significant effort.

Pricing and Plans

SAP Integrated Business Planning (IBP) pricing is not openly listed on the official SAP website and typically requires interested customers to request a personalized quote or demo based on their specific business needs and scale.

Best for
Large enterprises using SAP ERP that want integrated planning without creating separate islands of data.

6. Oracle Supply Chain Planning Cloud

Oracle’s supply chain planning suite is part of its cloud SCM offering.

Oracle combines demand management, constraint-based planning, and embedded machine learning to help customers manage end-to-end planning in the cloud. 

This AI supply chain analytics software platform suits organizations that prefer a large cloud vendor for single-vendor consolidation. 

Key features

• Constraint-based supply planning and what-if analysis.
  
  

• Demand management and demand sensing.
  
  

• Integrated analytics and forecasting.

Pros

• Cloud-native and integrates with Oracle’s wider SCM modules.
  
  

• Scalable for large enterprises and multi-country deployments.

Cons

• Users report UX and flexibility trade-offs in certain areas.
  
  

• Integration and customization benefit from experienced Oracle consultants.

Plan and Pricing

Oracle lists cloud pricing models for infrastructure; application pricing for SCM is custom.

Contact Oracle for a tailored quote and deployment options.

Best for
Enterprises seeking a cloud-first suite from a major vendor and that need deep functional breadth.

7. IBM Supply Chain Intelligence Suite

IBM supplies a suite of services and software focused on visibility, predictive insights, and orchestration.

The Sterling and Supply Chain Intelligence offerings combine AI, automation, and analytics to deliver aggregated views across data silos. 

IBM positions these offerings for companies handling complex order flows and large volumes of events.

Key features

• Aggregated visibility and predictive alerts.
  
  

• Order orchestration and fulfillment optimization.
  
  

• Integration with IBM Cloud offerings and enterprise systems.

Pros

• Strong capabilities for complex B2B and e-commerce order ecosystems.
  
  

• Enterprise-grade security and global support.

Cons

• Not always the fastest option for quick pilots.
  
  

• Requires integration and configuration effort.

Pricing and Plan

IBM’s pricing is enterprise-focused and often requires contacting IBM sales.

Some IBM Sterling B2B bundles have entry points listed for integration bundles.

Best for
Large enterprises with complex order orchestration needs or global e-commerce operations.

8. Infor Nexus

Infor Nexus focuses on multi-enterprise networks, connecting buyers, suppliers, carriers, and financial partners on a single platform.

It is strong on logistics visibility, supplier collaboration, and transportation tracking. 

Many companies use this AI supply chain analytics software platform as a control tower for multi-party visibility.

Key features

• End-to-end visibility across orders and shipments.
  
  

• Predictive alerts and intelligent decision support.
  
  

• Supplier collaboration and sustainability modules.

Pros

• Strong for multi-party collaboration and logistics visibility.
  
  

• Prebuilt transport and port integrations for global trade.

Cons

• Integration complexity when connecting a large partner network.
  
  

• Best value emerges when most trading partners adopt the network.

Pricing and Plan

Infor Nexus uses an enterprise subscription model and quotes are provided on request.

Best for
Retailers, brands, and manufacturers that need a shared network with suppliers and logistics partners.

9. John Galt Solutions

 John Galt Solutions offers Atlas, a planning platform with a reputation for fast implementations and strong forecasting. 

The AI supply chain analytics software platform targets organizations that want a practical, modular planning stack that can be deployed quickly and iterated upon.

Key features

• Forecasting and inventory planning modules.
  
  

• Low-code development environment and API marketplace.
  
  

• Rapid implementation templates for common use cases.

Pros

• Faster time to value in mid-market contexts.
  
  

• Responsive product updates and customer-driven enhancements.

Cons

• May lack some of the heavyweight digital twin or global modeling features of larger vendors.
  
  

• Requires data discipline for best results.

Pricing and Plan

John Galt markets Atlas as mid-market friendly. Public listings on software marketplaces require contacting sales for accurate quotes.

Best for
Mid-market manufacturers and distributors who need reliable forecasting and quick implementation.

10. ToolsGroup SO99+

ToolsGroup SO99+ is an AI-first planning and inventory optimization platform.

The product has a long history in demand sensing, multi-echelon inventory optimization, and service-driven planning. 

ToolsGroup promotes its ability to decode demand uncertainty and right-size inventory across networks.

Key features

• Service-driven inventory optimization and replenishment.
  
  

• Demand analytics capable of handling promotions and intermittent demand.
  
  

• NPI automation and transparency in forecasts.

Pros

• Strong multi-echelon inventory capabilities.
  
  

• Recognized in user reviews and industry awards.

Cons

• Some customers note implementation effort and the need for good data stewardship.
  
  

• Not always the cheapest option but focuses on measurable service-level gains.

Pricing and Plan

ToolsGroup provides pricing on request. Some marketplace listings show indicative starting figures but real quotes depend on SKU counts, network complexity and service requirements.

Best for
Retailers and distributors with complex replenishment needs and aggressive service targets.

How to Choose the Right Software for Your Needs

Selecting the correct solution requires matching vendor strengths to your immediate problems.

Here is a short decision checklist.

1. Define outcomes. Do you need better forecasts, lower inventory, faster response to disruptions, or supplier collaboration? Vendors excel at different outcomes.
   
   

2. Map data sources. List ERP, WMS, EDI, IoT, and partner feeds. Choose vendors with prebuilt connectors for your key systems.
   
   

3. Start small with a pilot. Run a single use case by SKU family or region. Measure forecast error reduction and inventory or service improvements.
   
   

4. Check total cost. Consider license fees, integration, training, and ongoing support. Some vendors are faster but less feature complete; others are deeper but cost more.
   
   

5. Validate support and managed services. Complex models need strong vendor support, especially if you have limited in-house data science resources.
   
   

6. Security and compliance. Confirm certificates and data handling practices if you move sensitive data to a vendor cloud.
   
   

7. Time to value. If you need traction in weeks, choose embedded analytics or mid-market platforms. If you want network-wide, enterprise-grade modeling, expect months.

Implementation and Change Management Notes

Deployments fail not because of analytics but because of people, process, and data.

Treat the project as a business change:

• Improve data hygiene before a pilot. Clean master data and SKU hierarchies matter more than model choice.
  
  

• Align S&OP stakeholders and set a clear decision owner for recommendations coming from the system.
  
  

• Start with a small scope and scale incrementally. Prove the ROI on a narrow SKU group, then expand.
  
  

• Invest in planner training and create a feedback loop so the models learn from corrections.
  
  

• Use vendor success teams and customer references to shorten learning curves.

Final Words: Practical Choices by Company Maturity

• Fast wins and product embedding: Upsolve AI. Use for dashboards, simple forecasting, and embeddable analytics. Good for product teams or when you need quick visibility and prebuilt roles.
  
  

• Mid-market manufacturers and distributors: John Galt Atlas. Fast implementations and strong forecasting.
  
  

• Retailers and distributors with complex replenishment: ToolsGroup SO99+. Proven multi-echelon optimization.
  
  

• Large global enterprises: SAP IBP, Oracle, Blue Yonder, o9, or Kinaxis depending on whether you prioritize ERP integration, cloud consolidation, digital twin simulation, or agile, concurrent planning. Validate each against real customer references and a proof of concept.
  
  

• Multi-enterprise visibility and trade: Infor Nexus. Use when supplier and carrier collaboration across countries matters.
  
  

• Order orchestration and complex e-commerce fulfillment: IBM Sterling for order orchestration and intelligence.

Frequently Asked Questions

1. Do I need machine learning expertise to use these tools?

Not necessarily. Many vendors provide built-in models and managed services. However, you must have domain knowledge to interpret results, set business rules, and maintain master data.

Vendors such as John Galt and Upsolve emphasize faster hand-holding for non-technical teams.

2. How long does it take to get value?

A pilot on a narrow SKU set or region can show measurable improvements in 8 to 16 weeks if data is in good shape. Enterprise-wide rollouts typically take longer.

Look for vendors that offer prebuilt connectors to reduce integration time.

3. Will these tools replace planners?

No. They augment planners by automating repetitive calculations and surfacing the right scenarios.

The best outcomes come when planners adopt AI recommendations and use their judgement for exceptions.

4. Which vendors provide multi-echelon inventory optimization?

ToolsGroup SO99+ is well known for multi-echelon optimization. Other vendors offer inventory modules, but the depth varies.

Confirm multi-echelon capabilities and ask for a sample model on your network.

5. Is data security a problem?

Security varies by vendor. Large vendors advertise enterprise-grade compliance. Always confirm SOC2, ISO, and regional data protections.

For networked platforms like Infor Nexus, verify how partner data is segregated.