AI for Distributors — Order Processing on Autopilot

For most formats, yes — and reliability is exactly why we keep a human approval step. The AI reads the PO, matches line items to your catalog, and flags anything it's unsure about rather than guessing. Your order desk reviews and approves. Over time, as it learns your customers' formats and your catalog, the share needing manual correction drops. We measure that accuracy during the pilot before you commit further.

In most cases, yes. We work with NetSuite, SAP Business One, Acumatica, Epicor, Sage, and others. How deep the integration goes depends on your system's API and whether you're cloud or on-prem. We assess exactly what's possible — and what the cleanest integration path is — during the free assessment.

AI doesn't replace your EDI infrastructure — it handles the exceptions that EDI kicks out. When an 850 fails validation because of an item-mapping or pricing mismatch, AI reads the problem, proposes the fix, and routes it with context instead of leaving a raw error for someone to decode. It makes your existing EDI flow less painful, not redundant.

No — it removes the repetitive volume so they handle more with the same team. The CSR bot answers routine status and availability questions; order intake automation eliminates re-keying. Your people move up to the work that needs judgment: problem accounts, complex orders, relationship management. Most distributors are trying to grow without proportionally growing the back office — this is how.

There's no hard cutoff, but the math works best when the order desk is a real cost center — say, multiple people spending most of their day on order entry, document handling, and status calls. If you're a small operation entering a handful of orders a day, off-the-shelf tools may be enough for now. The free assessment will tell you honestly which side of that line you're on.

Distributor data — customer lists, pricing, margins — is competitively sensitive. We encrypt data in transit and at rest, restrict access, and for the most sensitive workflows can run AI on private infrastructure rather than shared services. Your pricing and customer data is never used to train anyone else's model. We document the data-handling approach before building.