Case Studies/Real Estate & PropTech
Document Intelligence

Lease Intelligence Platform

Confidence-Scored Extraction & Portfolio Q&AA lease intelligence platform where every client owns a fully isolated environment, extracting structured terms from lease PDFs, answering portfolio questions with cited sources, and flagging low-confidence results for review.

IndustryReal Estate & PropTech
Statuspilot
PilotDocument AI
FastAPINext.jsPostgreSQLPgVectorLangChainOpenAICohereGroq

What we were solving for

Lease documents are long and inconsistent, and abstracting key terms by hand is slow and error-prone — with real legal and financial stakes if something is missed.

How we built it

Structured lease extraction

Tenant, rent, dates, and clauses pulled into typed fields, so portfolios can be filtered by date, term, or renewal.

Confidence scoring & citations

Every extracted field carries a confidence score linked back to its source text.

RAG-based portfolio chat

A chat interface answers questions across the whole lease portfolio, with sources cited on every answer.

Low-confidence flagging

An analytics dashboard surfaces low-confidence extractions and queries for attention.

Your own environment, not a shared tenant

No pooled infrastructure — your data, database, and encryption keys never touch another client's deployment.

Where it landed

Turns unstructured lease PDFs into structured, queryable data.

Every answer and extracted field comes with a confidence score and source citation.

Full data ownership and isolation, by default — not an add-on plan.

More Engineering Work

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