Data Extraction

Paragraph-by-paragraph AI extraction across documents, transcripts, emails, and reports at scale. Maps unstructured text into structured properties (objections, buying signals, risk indicators, renewal concerns, competitive mentions, action items) and entity-tied memories. Extract once, store as durable memory, reuse across every downstream workflow rather than re-paying token cost on every query that touches the same source.

Why it matters

Most of what a company knows is trapped in unstructured text (documents, transcripts, emails, reports) that nobody has time to read. Data Extraction turns that into structured, reusable signal at scale: objections, buying signals, risk indicators, renewal concerns, competitive mentions, action items. Extract once, and every downstream workflow reuses it instead of re-paying to parse the same source again.

How it works

Extraction runs paragraph by paragraph across sources, mapping text into structured properties and entity-tied memories. The output is durable, stored as memory against the right entity, so the cost is paid once and amortized across every query and agent that later touches the same material.