What does AI contract extraction actually do?
AI contract extraction reads a legal document and turns it into structured data: dates, costs, renewal terms, obligations. Done right, it replaces the most error-prone step in contract management — a human retyping what a document says.
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What it captures
From a lease or agreement, extraction identifies the fields a tracker needs: parties, agreement type, effective and end dates, renewal type and term, notice period, cost with currency and frequency, plus a plain-English summary and the document's concrete obligations. Derived values follow — most importantly the notice deadline (end date minus notice period).
How to judge accuracy claims
No extraction is perfect, so the design question is what happens when it's unsure. Trustworthy systems do three things: cite every value to the exact page it came from, attach a confidence score, and route uncertainty to a human instead of hiding it. Extraction without citations is a guess you can't check.
In Keep Track of Stuff, every value carries a page citation and confidence score; anything unverified is visibly flagged until someone confirms it — one click per field, or one click for all. Later amendments can't overwrite verified data silently; changes arrive as cited suggestions.
Extraction vs. OCR vs. chat
OCR converts an image to text — necessary for scans, but it doesn't know a notice period from a page number. Extraction is the semantic step: finding and structuring the terms. Chat is the retrieval layer on top: asking "which agreements auto-renew this year?" and getting a cited answer computed over the extracted data and the documents themselves.
Frequently asked questions
Is AI contract extraction the same as lease abstraction?
Functionally yes — lease abstraction is the commercial real estate term for extracting a lease's key terms into a structured summary, traditionally done by hand at a per-lease fee. AI extraction automates it, for leases and every other agreement type.
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