Private document intelligence

Private document RAG and OCR that feeds a living memory graph.

Oryne helps teams ask questions across PDFs, Word files, scanned images, and working documents while keeping the retrieval layer local or on-prem.

document RAG OCRprivate document AIPDF AI assistantlocal RAG assistantsecure document search AI

Primary search intent

document RAG OCR

Professionals and teams with sensitive documents that need AI search, summaries, and source-backed answers.

PDF, Word, Markdown, and scanned document workflows
OCR for image-based content
Graph memory links documents to people, projects, and decisions

What teams get

Searchable memory that turns context into action.

Ask questions across private files

Connect documents to meeting and inbox context

Find the source behind an answer quickly

Private RAG for real files

Teams rarely keep knowledge in one perfect wiki. Oryne indexes working documents and connects them to the rest of your memory graph.

  • PDF and document parsing
  • OCR for scans and screenshots
  • Chunking and embedding in private infrastructure

Documents become context

A document is more useful when the assistant knows who referenced it, which meeting changed it, and what commitments depend on it.

  • Document-to-person links
  • Decision and revision context
  • Cross-app source trails

Built for confidential material

Sensitive documents should not need to leave your environment to become searchable. Oryne keeps indexing and recall under your control.

  • Private embeddings
  • On-prem model support
  • No external training on source material

Questions

Common evaluation questions.

What is document RAG?

Document RAG retrieves relevant passages from files and supplies them to an AI assistant so answers can be grounded in source material.

Can Oryne work with scanned documents?

Yes. Oryne includes OCR-oriented workflows so image-based documents can be converted into searchable context.

Why connect documents to a memory graph?

A memory graph can link documents to people, decisions, meetings, and promises, which helps answer multi-step work questions.