Choosing a tool? Off-the-shelf AI rarely sees your TMS, WMS, ERP and carrier data. We build custom AI tools for logistics and supply chain teams that do.
What AI supply chain software actually does
AI supply chain software uses machine learning, optimisation and, more recently, language models and AI agents to make planning and execution decisions that teams used to make in spreadsheets: how much to make or buy, where to hold stock, which supplier to use, and what to do when a shipment is late. Most supply chain AI solutions sit on top of your ERP, TMS and WMS rather than replacing them.
This guide is for buyers comparing an AI supply chain platform for the first time. It covers the four main categories of software, ten tools that are established in each, a comparison table, how to choose, and when it makes more sense to build a smaller custom tool around your own data instead of buying a suite.
In practice, AI in the supply chain does a handful of jobs well:
- Forecasting demand from order history, promotions and outside signals
- Re-planning supply, inventory and capacity quickly when something changes
- Scoring suppliers on cost, lead time and risk, and finding alternatives
- Predicting arrival times and flagging shipments that are going to be late
- Directing warehouse work: waves, slotting, labour and replenishment
The four categories of AI supply chain platform
Planning and forecasting
Demand planning, supply planning, S&OP and integrated business planning. The AI forecasts demand and re-runs the plan when inputs change.
- Demand forecasting
- S&OP and IBP
- Scenario and what-if planning
- Network design
Procurement and supplier risk
Tools that read spend, part and supplier data to suggest sourcing decisions, and that monitor suppliers for financial, geopolitical and cyber risk.
- Should-cost and part analytics
- Supplier scoring
- Multi-tier risk mapping
- Tariff and sanctions exposure
Visibility and logistics
Real-time tracking across road, ocean, air and rail, with predicted ETAs and alerts, plus transport and trade management.
- Predicted arrival times
- Exception alerts
- Carrier and forwarder data
- Transport and trade compliance
Warehouse and inventory
Warehouse management and inventory optimisation, where the AI decides how work is released, who does it and how much stock to hold where.
- Wave and labour planning
- Slotting and replenishment
- Inventory positioning
- Order fulfilment
Planning and forecasting: 4 AI supply chain software tools
1. Kinaxis Maestro
Supply chain planning platform from Kinaxis, known until 2024 as RapidResponse. Built on concurrent planning: when demand, supply or capacity changes, the whole plan is recalculated quickly rather than in an overnight batch. Covers S&OP, demand, supply and capacity planning, with machine learning and a generative AI interface.
- Best for: manufacturers that re-plan often
- Strength: fast scenario comparison
2. o9 Solutions (Digital Brain)
Planning platform covering integrated business planning, S&OP, demand planning and supply planning, linking supply chain plans to commercial and financial plans. o9 is extending it from planning into execution.
- Best for: large, multi-brand organisations
- Strength: one plan across supply chain, commercial and finance
3. Blue Yonder
Owned by Panasonic. A broad suite spanning demand and supply planning, replenishment, warehouse management and transportation management, with machine learning forecasting and AI agents being added across the suite.
- Best for: retailers, grocers and distribution networks
- Strength: planning and execution from one vendor
4. Coupa Supply Chain Design & Planning (formerly LLamasoft)
Coupa bought LLamasoft in 2020. The product models your network of plants, warehouses and lanes so you can test where to make and store goods, how to route them and what a disruption would cost, before you commit.
- Best for: network design and strategic what-if questions
- Strength: modelling and simulation
Procurement and supplier risk: 2 tools
5. LevaData
AI platform for direct-materials sourcing. It combines a manufacturer's bill of materials with market data on parts and suppliers to suggest savings, flag risk and run sourcing events. Its AI advisor, Leva, answers sourcing questions in plain language.
- Best for: electronics and hardware manufacturers
- Strength: part-level cost and risk insight
6. Interos (interos.ai)
Supplier risk platform built on a knowledge graph of companies and their supplier relationships. It maps suppliers several tiers deep and monitors financial, cyber, geopolitical, reputational and tariff risk.
- Best for: risk and continuity teams with large supplier bases
- Strength: multi-tier visibility of who your suppliers depend on
Visibility and logistics: 3 tools
7. FourKites
Real-time visibility platform that tracks freight across modes, predicts arrival times and flags exceptions. In 2026 it added AI agents that act on those exceptions, for example in logistics execution, supplier collaboration and dock appointment scheduling.
- Best for: shippers and 3PLs with multimodal freight
- Strength: carrier network and predicted ETAs
8. project44 (now including ClearMetal)
Visibility and decision intelligence platform. project44 acquired ClearMetal in 2021, bringing its machine learning for predicted ETAs and inventory-in-transit visibility into the platform. In 2026 it added a conversational AI analyst that answers questions over a customer's own shipment data.
- Best for: shippers wanting order and inventory visibility, not just tracking
- Strength: logistics data network
9. E2open (now part of WiseTech Global)
WiseTech Global completed its acquisition of E2open in August 2025. E2open covers demand and supply planning, channel data, supplier collaboration, transportation and global trade management for multi-party supply chains.
- Best for: global enterprises with complex trade and partner networks
- Strength: collaboration across suppliers, carriers and channels
Warehouse and inventory: 1 tool
10. Manhattan Associates (Manhattan Active)
Warehouse management, transportation and omnichannel order software on one cloud platform. Since January 2026 it ships AI agents inside its products: assistants for warehouse roles, and background agents that watch operations and fix issues such as wave planning and labour allocation.
- Best for: high-volume distribution and fulfilment centres
- Strength: warehouse execution
AI supply chain software compared
| Tool | Category | Main AI use | Typical buyer |
|---|---|---|---|
| Kinaxis Maestro | Planning | Concurrent planning and scenario re-planning | Manufacturers |
| o9 Solutions | Planning | Integrated business planning, demand forecasting | Large multi-brand enterprises |
| Blue Yonder | Planning and execution | Forecasting, replenishment, warehouse and transport | Retail and distribution |
| Coupa Supply Chain Design & Planning | Planning (network design) | Network modelling and simulation | Strategy and network teams |
| LevaData | Procurement | Part-level cost, risk and sourcing advice | Direct-materials procurement |
| Interos | Supplier risk | Multi-tier supplier mapping and risk monitoring | Risk and continuity teams |
| FourKites | Visibility | Predicted ETAs, exception handling agents | Shippers and 3PLs |
| project44 | Visibility | Predicted ETAs, inventory in transit, AI analyst | Shippers |
| E2open (WiseTech Global) | Planning, logistics and trade | Multi-party planning and trade management | Global enterprises |
| Manhattan Associates | Warehouse and inventory | Warehouse AI agents, wave and labour planning | Distribution centres |
None of these vendors publish list prices; all are quoted per customer, and most are sold as multi-year enterprise subscriptions with an implementation project on top. If you are a logistics business rather than a shipper, our list of AI tools for the logistics industry covers carrier, forwarder and fleet software.
How to choose an AI supply chain platform
Name the decision, not the technology
Write down the one decision you want made better: the weekly forecast, which supplier to award, which shipments to expedite. That tells you which of the four categories you are shopping in.
Check your data before the demo
Every AI supply chain solution depends on clean item, supplier, location and order data. If your masters are inconsistent across ERP and spreadsheets, the model will forecast the inconsistency. Fixing this first often matters more than the choice of vendor.
Ask how the AI explains itself
Planners will override a forecast or recommendation they cannot understand. Ask each vendor to show why the system made a specific recommendation on your own data, not a sample dataset.
Count the integration work
Ask which connectors to your ERP, TMS and WMS already exist, who builds the rest, and how long a comparable customer took to go live.
Pilot one flow and measure it
Run a time-boxed pilot on one product family, lane or supplier group, and agree the measure beforehand: forecast error, expedite cost, hours of manual work removed.
When to build custom supply chain AI instead of buying
The platforms above are built for large enterprises with planning teams and long implementation budgets. Many supply chain problems are smaller and more specific: one manual process that eats a team's week, or one data source no product reads. In those cases a custom tool built around your own data is usually faster to deliver and cheaper to run than a platform licence.
Custom tends to win when:
- The work is a repeatable manual process (searching, qualifying, chasing, copying) rather than a planning problem
- Your data lives in emails, PDFs, supplier websites or spreadsheets that platforms do not ingest
- You need the output inside tools you already use, such as a sheet, a dashboard, email or WhatsApp
- You want to prove the value on one process before committing to a suite
This is the work Greenwolf does through our supply chain automation services. For a France-based supply chain company, we automated their manual supplier scouting process, replacing Google searches and hand-applied filtering rules with an automated pipeline that cut the time spent by 85 percent and the cost by 91 percent. We also run supplier identification and qualification work, where AI gathers and structures supplier data so qualification teams start from a shortlist rather than a blank search.
On the logistics side, we build shipment status updates that send themselves, reading carrier emails and tracking feeds and telling customers when an ETA moves, and we automated delivery route planning for a UK logistics company. To see how a supply chain is performing once the data is clean, see our supply chain performance dashboards.
AI supply chain software: common questions
What is AI supply chain software?
What is the best AI for supply chain management?
How is AI used in supply chain management?
What is the difference between an AI supply chain platform and a custom AI solution?
Do small and mid-sized companies need AI supply chain software?
What data do supply chain AI solutions need?
Have a supply chain process that should run itself?
Tell us the process and the tools it runs on. We will tell you whether a platform, a custom build or a simple automation is the right fit.
Part of our Supply Chain and Procurement hub. Start with our supply chain automation.