More automation
Let the system infer, extract, and decide more. Faster cycles — and a thinner trail when something looks wrong.
Case study · Agentic AI
Contract to Invoice
Agentic AI for a real finance workflow
You’re the finance lead staring at university contracts that refuse to look the same. Clauses hide in different places. Commission logic depends on who signed what. The invoice still has to be right — every cycle.
A fork in the approach
Every technical path was available. The question wasn’t “can AI read a PDF?” — it was which risks the business was willing to carry.
More human review
Keep more checks, exceptions, and approvals. Safer on day one — slower when volume climbs.
The business requirement picked the path: accuracy and explainability over black-box speed. Agentic extraction with selective human oversight — not autopilot.
How the system earned trust
Understand the mess
Contracts arrive unstructured. Formats drift. The first job is mapping variability — not writing prompts.
Define what matters
Only the fields that drive commission and audit survive. Everything else is noise with a cost.
Agentic, not autopilot
OCR + LLM orchestration + business rules — with a traceable path when the model is unsure.
Close the loop
Verified terms feed invoice generation under policy checks. Finance stays in control of the last mile.
Hours of manual finance effort removed each cycle — without pretending contracts were ever tidy data.