Industries / Supply chain
AI agents for supply chain, working together.
AI in supply chain means specialised agents that monitor, coordinate and handle routine work across ERP, suppliers, carriers and warehouses. Your team owns the exceptions and the strategy.
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What we can build for supply chain. Not one assistant, but specialised agents that hand work to each other.
Demand sensing and replenishment
Agents that spot demand changes, check stock across warehouses and propose replenishment.
Supplier risk monitoring
Continuous tracking of supplier performance, with risks and alternatives raised before they cause delays.
Purchase order exceptions
Contract mismatches, missing confirmations and late orders detected, with routine fixes handled automatically.
Disruption recovery
When shipments slip, agents compare routes and carriers and draft customer updates for approval.
Warehouse balancing
Stock rebalanced between sites, including expiry-sensitive inventory.
Production scheduling support
Schedules adjusted for demand, capacity, maintenance and material availability, for planners to approve.
Customer order updates
Accurate order promises, early delay notices, and triage of claims and returns.
Trade document intelligence
Data extracted from invoices, confirmations and shipping documents, with exceptions routed to people.
Built on your systems
Agents work across your ERP, supplier portals and carrier data, with an audit trail for every action.
Freight invoice audit
Carrier invoices matched to shipments, with mismatches flagged.
Supplier onboarding
Supplier documents collected and checked, with missing items chased automatically.
Inventory exception alerts
Stock mismatches across warehouses flagged with a suggested action.
Match the autonomy to the task. Routine work runs on its own. People own the exceptions and the strategy.
- L1WorkflowA fixed, auditable path.
- L2AssistantAI drafts. A person reviews.
- L3Supervised agentAI acts and flags exceptions.
- L4AutonomousRoutine, low-risk, monitored.
- Human-ledPeople decideAI supports the analysis.
Demand sensing and replenishment
Agents detect changes and propose orders. Planners approve.
L3 Supervised agentSupplier risk monitoring
Continuous monitoring, with risks and alternatives flagged to the team.
L3 Supervised agentRoutine purchase order exceptions
Low-risk, repeatable fixes handled automatically and monitored.
L4 AutonomousDisruption recovery and customer updates
Agents propose new routes and draft updates. The team approves.
L3 Supervised agentCompliant shipments
A fixed, auditable workflow for regulated goods, with agents tracking approvals.
L1 WorkflowL3 Supervised agentSourcing strategy and key suppliers
Strategic decisions stay with people, supported by the agents' analysis.
Human-led
Related work from other industries. We have not yet delivered a supply chain project. These engagements built the same kinds of systems.
AI agent platform
Agents retrieve, reason and act across systems, with human approval before high-stakes actions.
~40% less manual effort AI · Document intelligenceAI document intelligence
Extraction and classification that sends only the exceptions to people.
>80% less manual review AI · Workflow automationWorkflow automation platform
AI extraction feeding a deterministic rules engine, with consistency checks built in.
~70% faster document prepHave a supply chain process that needs constant manual follow-up?
The technology we would use for supply chain. Chosen for agents that read ERP, supplier and carrier data and hand work to each other.
01 / 06
Agents and orchestration
How agents plan, call tools and hand work to each other.
AutoGen- CrewAI
02 / 06
Models
The language models behind each feature, picked per task on cost, speed and quality.
- OpenAI
- Anthropic Claude
- Google Gemini
- LangChain
03 / 06
Data pipelines
Moving and preparing data so models see the right, fresh inputs.
- Apache Kafka
- Apache Airflow
- Apache Spark
- dbt
04 / 06
Databases
Where product data lives.
- PostgreSQL
- Snowflake
- MongoDB
- Redis
05 / 06
Cloud and infrastructure
Where it runs, in your cloud or ours.
- AWS
- Microsoft Azure
- Google Cloud
06 / 06
Evals and operations
Tracing, testing and monitoring once it is live.
- Langfuse
From one handoff to a team of agents. Four stages, with your planners reviewing every flow at each one.
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Discovery
Map the process, the systems and data involved, and what good looks like.
Discovery notes
- The systems, partners and data involved
- Where manual follow-up sits today
- Approval rules
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Scope & architecture
Agree each agent’s role, the handoffs between agents and the approval rules.
Solution design
- Agent roles and handoffs
- Approval checkpoints
- Success measures
-
Build
Build against ERP, supplier and carrier data, with planners reviewing every flow.
Working build
- Working agents on real data
- Team review of every flow
- Exception tests
-
Ship & support
Roll out with approval checkpoints, exception handling and a defined support window.
Production rollout
- Production rollout
- Monitoring
- Support window
Why Avinya for supply chain. Agent systems that act across business systems, already in production elsewhere.
Agents across systems
Our agent platform retrieves, reasons and acts across business systems, with about 40% less manual effort in one engagement.
Human approval by design
A human checkpoint before any high-stakes action.
Exceptions, not everything
Our document systems route only the exceptions to people.
Honest about fit
We tell you which tasks need an agent and which need a simple workflow.
Engagement models. Pick the shape that fits where you are.
Dedicated team
A team that extends yours as suppliers, carriers and systems are added.
Project-based
A defined scope for one flow, such as purchase order exceptions, with milestones and a delivery date.
Consulting & advisory
Advice on which tasks need agents and which need a simple workflow, before you commit to a build.
What our clients say.
AI platform for an insurance broker
“Avinya Labs built our full-stack AI solution … Their expertise accelerated our launch and significantly reduced execution risk.”
Guides on this topic. Plain answers to the questions buyers ask first.
Operational AI Systems: A 2026 Guide for Enterprises
How AI moves from pilots into the daily operations of a business.
Read the guide → GuideAgentic Commerce: How AI Agents Shop and Pay (2026)
How AI agents search, decide and pay on behalf of shoppers, and what to build first.
Read the guide → GuideEnterprise AI Deployment: Why Projects Stall in Pilot
The eight causes we see most, and a roadmap that gets AI live.
Read the guide →AI for supply chain FAQs.
Have you delivered a supply chain project before?
Not yet. We have built the same kinds of systems in other industries: agent platforms that act across business systems, document intelligence and workflow automation. Those engagements are linked on this page.
Why several agents instead of one assistant?
Supply chain work spans planning, procurement, logistics and customer service. Specialised agents can each do one job well and hand work to each other, with people approving the decisions that matter.
Which systems can the agents work with?
ERP, supplier portals, carrier data and warehouse systems, depending on what you run. Integrations are agreed during discovery.
Where should a supply chain team start?
With one flow that needs constant manual follow-up, such as purchase order exceptions. We map the systems and approvals, agree what good looks like, and build a working version planners can review.
How is supplier and order data handled?
Access is scoped per agent and per role, and every action is logged for review. Where data lives and which models can see it are agreed during discovery.
Which AI models do you use?
We evaluate models against your real flows and choose per agent, so routine steps can run on a cheaper model. The design lets models change later without rebuilding the system.
How long does a project take?
A prototype on one flow takes about 6 to 9 weeks and a first version planners can review about 8 to 12 weeks. A production rollout across systems typically takes 3 to 5 months.
Can we sign an NDA first?
Supplier and pricing data is commercially sensitive. Yes. We can sign an NDA before you share anything, and we agree ownership of the work in the contract before the work starts.
Where does AI in supply chain work usually start?
With documents and exceptions: orders, invoices and delay notices that people re-key today. We have not delivered a supply chain project, so we scope AI in supply chain as a discovery step and use the NIST AI Risk Management Framework to review risk.
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