Document AutomationConstruction contractor · Florida

AI material price database

A working proof-of-concept that turns a 1,000-supplier price catalog from a manually-typed wishlist into a self-updating database — fed by PDFs and phone photos today, with email ingestion planned for the pilot.

Working demo · pilot in scoping
1,000
Suppliers tracked
20
Columns auto-filled
~4 hrs
Saved per week
PDF · Photo
Doc types handled

The problem

The client is a general contractor in Florida — a small ops team running dozens of active jobs and dealing with hundreds of suppliers a year. Their Google Sheet had every supplier name in it. Almost no actual prices.

Every supplier sends data differently: a printed receipt from the lumber yard, a PDF quote attached to an email, a phone snap of a Home Depot invoice, a forwarded spec sheet from Sika or GAF. Their PM was retyping these one by one — when she had time, which was rarely. Most rows just never got priced. So bidding new jobs ran on last quarter's pricing and gut feel.

The pain wasn't lack of software. They'd already tried two SaaS tools. The pain was: no tool actually does the boring work of reading a crumpled receipt and turning it into structured rows in their sheet, with their item naming and their supplier IDs.

What we built (working demo)

A document pipeline that lives where their team already works — Google Drive and Google Sheets. No new app to learn. The pieces below are all working in the demo we walked the client through; the paid pilot is being scoped now.

What we deliberately did not build (yet)

We made a few sharp decisions to keep the MVP cheap and useful instead of overengineered:

The architecture, in one breath

Watched-folder ingestion → document classifier → model router (OpenRouter — 6 models, picked per document type) → structured extraction → fuzzy supplier match → dedup → review queue → approved rows written to the client's Sheet via Apps Script webhook with a secret token. Source docs uploaded to private Drive, every Sheet row holds a link back.

Where it stands

Demo signed off by the client's PM, NDA in place, paid pilot being scoped. The pilot will move it off the founder's laptop onto real hosting, add proper multi-user auth and email-ingestion, and ship a mobile photo upload for the field crew. Phase 2 — Postgres, audit log, real-time price-anomaly alerts ("SIKA went up 15% this month") — sits on the roadmap after that.

Why this matters beyond one client

This pattern — turning unstructured supplier docs into structured rows — is the same shape that hits accountants, law firms, logistics, insurance, property management, and medical billing. We took the slowest, most expensive piece of someone's week and made it disappear. If that's a process you recognize in your own business, the discovery call is 15 minutes.

Want this kind of system inside your business?

Every project starts with a 15-minute discovery call. We map your workflow, find the highest-impact automation, and tell you up front whether it's worth building.