Xeven Labs
All workAI SaaS

AI-Powered Matching Engine

Scores listings against buyer/tenant criteria by parsing unstructured PDF requirement docs.

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The Challenge

Built an AI engine that scores listings against buyer/tenant requirement criteria automatically. The hard part: parsing unstructured PDF requirement documents in inconsistent formats and reliably extracting structured criteria for the AI to score against — with a live database keeping the pipeline updated in real time.

Our Approach

We built a parsing layer that extracts structured criteria from inconsistent PDF formats before scoring runs, keeping a live database in sync so new listings are scored against current requirements automatically.

The Impact

Matching that used to require someone manually reading requirement documents and listings side by side now happens automatically, with scores that update as new listings come in.

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