AI workflow automation across your business systems

A purchase order arrives by email, is read, checked against the customer’s credit limit and entered as a sales order. A new client signs, and their accounts, folders and kickoff tasks are created. A supplier invoice is matched to its PO and routed for approval. Each one mixes fixed rules, an AI step that reads or decides, and a person on the exceptions.

Those tools connect apps with triggers and simple steps, and they do that well. We design the whole process, including steps that need reading documents or making decisions, add approvals and error handling, and run it in production with monitoring. If your team already runs n8n, Make or Zapier, we can build on top of it.

Yes, when one process eats several hours a week and follows rules you could write down. Start with that one workflow and a fixed scope. If the process changes every month or happens a few times a quarter, a checklist is usually cheaper than automation.

Classic business process automation follows fixed rules and stops when the input is messy. Adding AI lets the workflow read emails and PDFs, classify requests and draft replies, so more of the process runs without a person. That mix is often called intelligent workflow automation. The rules and approvals stay, and they decide what the AI is allowed to do.

A project usually starts with an audit of how the process runs today, then covers the build, testing on your past cases and a run phase with monitoring. We do the mapping, build and upkeep, and you approve the exception rules. Tool comparisons are in our workflow automation software guide.

Failed steps retry automatically, then alert the owner with the error and the data involved. Every failure is logged and visible in the console until someone resolves it.

Order and booking handling, client onboarding, approvals, compliance checks, internal requests, reporting, and keeping records in sync between systems.