Warranty documents that read themselves
Confidential · ConTech
The business said
- “Hire a claims coordinator for every property”
- “Keep a master spreadsheet of warranty PDFs”
- “Scan everything into folders and hope”
- “Build a separate portal nobody will open”
- “Extract every warranty's terms with AI, inside the tool teams already live in”
Missed warranty deadlines were not a diligence problem. They were an extraction problem: the terms were buried in PDFs nobody had time to read.
A retrieval-augmented extraction pipeline, embedded in Procore
A developer of commercial buildings and tech parks tracked warranties by hand. Every project handed over stacks of PDFs, and the facilities team had to remember which vendor covered what, until when, under which conditions. When something broke, working out whether the repair was still free took days, and sometimes the deadline had already passed unnoticed. The manual system did not fail loudly; it just quietly leaked money.
We built the fix inside the software the team already used. An embedded app in Procore, the construction management platform, pulls every warranty document attached to a project. A custom retrieval-augmented generation pipeline, written in Python with LangChain on top of the cloud provider's managed AI models, reads each document and extracts the terms that matter: coverage, vendor, start date, and the expiration that keeps getting missed. Claims are auto-categorized into trades such as plumbing and electrical, and the team manages claims, reports, and vendor emails without ever leaving Procore.
The accuracy came from method, not magic. We started with sample documents from the client, tested whether generative extraction could beat the manual baseline, and then tuned prompts across a large and messy document set until the answers held up. A demo app let the client upload any document, see the extracted terms, and ask follow-up questions of the document itself before the Procore integration went in.
The result is a warranty register that maintains itself. Deadlines surface before they lapse rather than after, categorization happens on ingest, and the question "is this covered" is answered by the documents, not by whoever has been around longest. The team kept their tool and lost their spreadsheet.
- RAG on managed AI, extraction
- Procore, lives inside
- auto categorized, claims
- surfaced, not missed, deadlines
- built-in Q&A, ask the doc
