Inside SNAP's capture layer: how pages, decks, PDFs, and voice notes become retrievable…
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A feature deep-dive on SNAP's capture layer — the ingestion pipeline that turns everyday work artifacts into a governed, retrievable enterprise graph.
Enterprise AI fails when the model is smart but the inputs are scattered. SNAP's capture layer is the ingestion pipeline that closes that gap — turning the messy artifacts of daily work into structured, retrievable memory without asking people to change how they work.
What capture actually ingests
- Documents — PDFs, Word, slide decks, spreadsheets, and long-form pages, parsed with layout awareness so tables, headings, and figures survive.
- Screens and images — screenshots and diagrams run through OCR and vision analysis so text-in-image is retrievable alongside typed content.
- Voice and meetings — voice notes and call recordings transcribed, speaker-attributed, and linked back to related projects.
- Web and app context — pages captured in the moment they matter, with source URL and timestamp preserved.
From artifact to graph node
Every capture is analyzed, chunked, embedded, and linked into the enterprise knowledge graph. Entities — people, projects, products, customers — are resolved across sources so a mention in a deck connects to the same node as a mention in a transcript. That's what lets reasoning search later cross documents instead of matching keywords.
Governance is a first-class capture concern
Capture inherits tenant isolation, role-based access, and an audit trail from the moment content enters the system. Contributors see only what their role permits; admins can trace every answer back to the exact captured artifact. For the governance model in detail, see Governance Inside SNAP. For how captures become reasoning-ready, see the enterprise knowledge graph deep-dive.