Most "AI projects" stop at a chat box bolted onto a help centre. It answers questions, sometimes well, and then hands the user back a to-do list. The work still happens by hand.
An agent is different. It has tools, permissions, and a definition of "done." It reads the invoice, checks it against the PO, routes the exception, and updates the ledger — then tells a human only when judgment is actually required.
Why most agent projects fail
They fail for boring reasons: no evals, no guardrails, and no clear hand-off to a human. We treat those three as non-negotiable from day one. An agent without evals is a demo, not a system.
What we ship instead
Scoped agents with measurable success criteria, a human-in-the-loop on the exceptions, and logging you can audit. Smaller surface area, higher reliability, real ROI.