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AI agents for procurement, from request to payment

Agents for the paperwork around every purchase

Agents check purchase requests, compare supplier offers and match invoices, with a person approving every commitment you choose.

Book a free consultation How we build agents
purchasing-desk

  1. Operations leadYour team

    We need a replacement pump for the packing line by next week. Can the purchasing agent handle the order?

  2. Purchasing agentAgent

    1. catalogue.search approved suppliers for the part
    2. contracts.get_terms framework price and delivery
    3. budget.check cost centre budget left
    4. po.draft purchase order for the pump

    The order is drafted with your framework supplier. It is above your approval limit, so it needs a sign-off.

    Needs a personOrder above your approval limitPurchase order for a replacement pump
    Approved by Procurement lead

  3. Purchasing agentAgent

    1. erp.create_po approved order sent

    Order sent to the supplier. When the invoice arrives, it is matched to this order and the delivery note.

Example data. An agent at work in a team channel, with a person approving the step you choose.
Mixam: conversion to a final sale from about 20% to about 40%
Where agents help

Purchases slow down in the checks around them.

Agents do the reading and checking and hand back the decisions that need a person.

  1. 01

    Where it stallsPurchase requests wait for someone to check them.

    What we do An agent checks each request against budgets, catalogues and contracts and drafts the order for approval.

  2. 02

    Where it stallsComparing supplier offers takes days of reading.

    What we do Agents line up price, terms and delivery from each quote and flag clauses that differ from yours.

  3. 03

    Where it stallsInvoices that do not match the order block payment.

    What we do Matching runs in code. An agent explains each mismatch and drafts the question to the supplier.

What we build

What we build for procurement teams

Whatever comes in, every project is built from the same parts below, set up for your files and your systems.

Procurement work we take on

  • Purchase requests
  • Purchase orders
  • Supplier quotes
  • Contract comparison
  • Invoice matching
  • Supplier onboarding
  • Spend questions
  • Approval routing

How we build it

  • Purchase request and order agents

    Requests checked against catalogues, budgets and contracts, and orders drafted for approval.

  • Supplier quote and contract comparison

    Quotes and contracts read side by side, with clauses that differ from your terms flagged.

  • Invoice matching inside your ERP

    Order, delivery note and invoice pulled from your ERP and matched in code, with each exception explained.

  • Approval rules your team agrees

    Spend limits, preferred suppliers and escalation rules agreed with procurement and enforced in the system.

Not seeing your case? Bring the buying step that waits longest and we start from that.

Tell us about your workflow
How we build agents

Agents that work as part of your team

They work in the tools your team already uses, take on whole tasks and stop for a person where you decide.

  1. Routines: agents that start on a schedule, on new GitHub issues or on an API delivery.
  2. Connected systems: GitHub, Linear, Notion, Slack, Jira and other tools an agent may call, each connected with its own sign-in.
  3. Approvals log: each action that waited for a person, with who asked, who decided and when.
Routines: agents that start on a schedule, on new GitHub issues or on an API delivery.
Connected systems: GitHub, Linear, Notion, Slack, Jira and other tools an agent may call, each connected with its own sign-in.
Approvals log: each action that waited for a person, with who asked, who decided and when.

Screens from the workspace our agents run in, with example data.

Industries

Industries we build agents for

Each page shows where agents fit in that industry and what we have built there.

All industries
Engineering in the open

We help build what agentic AI runs on

Open standards, open-source tooling and published research, all public, so you can check our engineering before you hire us.

Shaping agentic AI

Agentic AI Foundation

Vstorm was the first agentic AI engineering company to join the Agentic AI Foundation and received its 2026 Open Agentic AI Innovation Award.

Read the announcement

Open source

We build open-source agent tooling that other engineering teams install

10M+ PyPI downloads
4,000+ GitHub stars
33 public repositories

Framework contributors

When the framework breaks, we fix it at the source

We maintain our own open-source agent framework and contribute fixes to the frameworks our agents run on, through official partnerships with their teams. Breaking changes reach us before they reach your codebase.

Research

Our engineers and PhDs publish peer-reviewed research

Peer-reviewed papers on agent architectures, evaluation and AI security, and an open benchmark anyone can rerun against our results.

Track record

Frontier AI teams now build on what we shipped first

Our client agents were in production before most of today's agent frameworks had a stable release. You get a team that already knows what breaks between a promising demo and a system people rely on every day.

Case studies
All case studies
Engagement models

Ways to start

Each path starts with a free call with a founder or senior AI engineer. A build goes ahead only after its Proof of Value meets the agreed threshold.

Start with one workflow

We map one workflow with your experts and agree a success threshold before any build.

Best whenYou want the success test agreed before you commit to a build.

Book a free consultation
  1. Process redesign and build Best whenYou want one team accountable for the outcome.
FAQ

Questions about AI agents for procurement

What are AI agents for procurement? +
AI agents for procurement are software agents that handle the reading and checking around each purchase: purchase requests, supplier quotes, contracts and invoices. They work inside your ERP, email and contract store with the access you give them. Prices and spend limits stay in tested code, and a person approves every order or exception you choose.
Where does agentic AI in procurement help first? +
Start where requests or documents queue up behind a few people: purchase requests checked against budgets and contracts, invoices that fail the match with the order, or supplier quotes waiting to be compared. We map the process with your procurement lead, pick one step, agree a success threshold and test the agent on your own past orders.
Have you built AI agents for procurement? +
There is no published case for a procurement workflow yet. The closest builds handle the same kinds of documents and data. For a US health insurer, claim processing was cut from 3 hours to 8 minutes, with a specialist still deciding. Real estate due diligence was cut from weeks to minutes. For a US manufacturer, questions are answered in SQL over 473+ columns across 15 database views.
How do agents keep purchase orders and payments correct? +
Spend limits, framework prices and matching rules run in tested code. The agent reads documents and drafts the next step, and the code decides whether the numbers match. Nothing goes to a supplier or is released for payment without the approval you set, and every step is logged with its source documents for audit.
How do you know it works before the full build? +
We agree a success threshold with your team before the build and test the agent on your own cases in a Proof of Value. It measures accuracy and running costs, and the build goes ahead only when the threshold is met. Corrections from your team go back into the test set, so every later version is checked against them.
Who owns the system, and which models does it run on? +
You own the code, prompts, evaluation sets and rules by contract. The agents run in your environment on hosted or open-weight models. The model sits behind an interface in code, so you can change it when accuracy, speed or your hosting rules change, without rebuilding the agent.
Start with one workflow

Test one workflow on your own data

A Proof of Value shows accuracy and running costs before the full build.

Book a free consultationRead case studies