A mid-market legal-tech company was using AI to extract indemnity, termination, and payment clauses from incoming contracts. The AI was 92% right. The 8% it got wrong cost their customers an average of $40k per missed clause.
A misextracted indemnity clause can leave a customer liable for damages their counterparty thought were excluded. The AI's confidence score didn't catch all the edge cases — clauses split across pages, footnoted modifications, "notwithstanding the foregoing" rewrites. They needed a human verification layer that didn't bottleneck their throughput.
On every clause the AI extracted, they call verify_document() with the source page and the AI's draft. A reviewer confirms the bounding box, the exact text, and the clause classification before the typed object flows into the customer's report.
from awaithumans import AwaitHumans client = AwaitHumans(api_key="ah_sk_live_...") verified = await client.verify_document( task_description="Verify clause type, bounds, and exact text.", response_schema=Clause, document_path=contract.path, prior_extraction=ai_extraction, # reviewer sees AI guess + source priority="standard", )
“We could've built a paralegal review tool. We would've spent six months on it. We integrated AwaitVerify in two days and the typed clause objects dropped right into our existing pipeline.”— VP Product, mid-market legal tech