Featured customerAgents read any order format and create the order in the ERP, with the team reviewing only exceptions.
- of orders need no touch
- >90%
- processing time per order
- <1 min
- staff effort reduction
- 85%
AI agents for supply chain & distribution
Your orders, invoices, CoAs, and SDSs arrive through your channels and land in your systems of record, ERP included. Agents work both ways. Your team takes the exceptions.
Built for distributors and manufacturers who run on shared inboxes, portals, EDI, and an ERP.
Four bands. At the top, an operations hub where your team and your agents share one queue, with agents processing and people approving the exceptions. Beneath it, a band of AI agents for quotes, orders, invoice matching, CoA and SDS documents, plus agents you build yourself. Both rest on two equal foundations shown side by side: intake channels (email, customer portals, EDI, and uploads) and systems of record (ERP, accounting, and document repositories). Each foundation is joined to the agents by a two-way connector: agents read from both and write back to both.
Trusted by leading distributors and manufacturers
How it fits together
Your solutions rest on two hubs, and both rest on the systems you already run.
where your team and AI agents work side by side
AI agents that carry out your business logic, workflows, and rules
the systems your team already works in
One product, two hubs
Everything ships ready to run, and every part of it is yours to change.
Build and publish the AI agents and agent systems that encode your business logic: extraction, matching, approvals, ERP writes.
Run the business on top of them: live transactions, stages, exceptions, and human-in-the-loop approvals in the Quote to Cash (Q2C), Procure to Pay (P2P), and Quality Management (QM) centers.
One product: agents built in one hub do the work your team supervises in the other.
45–60
days DSO with manual workflows, against 30
2–3 hrs
per rep per day lost to manual document handling
$50K
typical cost of a single compliance violation
Solutions
78% of B2B buyers choose the vendor who responds first
Part of the Quote to Cash (Q2C) Center
2–5% of manually entered orders carry an error
Part of the Quote to Cash (Q2C) Center
Nobody owns it. The work arrives as attachments in a shared inbox, and it waits there for a person.
Part of the Agent Center
5–8% of supplier and freight invoices carry a billing error: money overpaid, or never billed back to the customer
Part of the Procure to Pay (P2P) Center
79% of companies have no automation for the supplier quality documents they receive
Part of the Quality Management (QM) Center
Every revision means re-papering an SDS by hand, and manual chasing never keeps up.
Part of the Quality Management (QM) Center
You get a working solution, not just a tool
The 50/30 guarantee
Our solutioning team builds your working solution with 50% down. Run it on your real documents for 30 days, and walk away owing nothing if you are not satisfied.
Prefer to see it on your own documents first? Book a demo · or read how we work.
Customer proof
5,000,000+
emails, tickets, and messages read by AI
100,000+
hours saved by our clients
2,000,000+
pages of documents and attachments read by AI
Featured customerAgents read any order format and create the order in the ERP, with the team reviewing only exceptions.
Design partnerAgents extract base rates, surcharges, and accessorials as line items and match every invoice before payment.
Design partnerAgents extract, validate against spec, and file every CoA, flagging only what needs a human.
Still deciding whether this is for you
A Gartner prediction and an MIT study looked at why AI projects go wrong, and named different causes. Neither named the models. Our reading, after doing this work with distributors, is that almost everything on both lists is settled while the work is being scoped, which is the cheapest moment to get it right.
Over 40%
of agentic AI projects are predicted to be cancelled by the end of 2027
Gartner names three causes: escalating costs, unclear business value, and inadequate risk controls.
95%
of enterprise generative AI pilots show no measurable P&L impact
The study attributes this not to model quality but to pilots that never integrated deeply into a specific workflow, and to systems that do not learn from feedback.
MIT Project NANDA
Bring one operation that hurts. We map how it runs today, what agents would own, what stays with a person, and what your systems actually support. You leave with a scoped plan you can take to your leadership, and you keep it whether or not you buy anything.
A map of how the operation actually runs
Where work arrives, who touches it, where it stalls, and which systems hold the truth, drawn in one place.
A ranked shortlist of what to automate first
Ordered by value against effort, with the reasoning shown. The first workflow decides whether the second one ever happens.
The line between agent work and human judgment
Which decisions agents should own outright, which come to a person, and what a reviewer needs in front of them to decide in seconds.
Our senior leadership runs these sessions personally, and takes 5 a month.
The people on the call are the people who scope the build and stand behind the guarantee, so the number is limited by their calendar rather than by a sales quota. When a month is full, the next open time is the following month.
No cost, no obligation, and no slideware. Read how we work first if you would rather.
See your own quotes, orders, and invoices processed in minutes.
Encryption, tenant isolation, and human review. Trust & security