Engagement letters routinely prohibit sharing client data with third parties — including cloud AI vendors. PrivateDocs AI lets consultants chat with the data room, prior deliverables, and interview notes on their own laptop, with cited answers and zero egress.
Alternatives replaced: ChatGPT Enterprise · Claude Team · Microsoft Copilot for Microsoft 365 · Glean · Notion AI
Drop the client's data room, working files, and prior deliverables into a local vault — and ask cited questions without breaching the engagement letter.
Drag the client's data room, prior deliverables, and interview notes into the desktop app. PDFs, Office files, and CSVs are all ingested natively.
Files are embedded and stored in a local ChromaDB vault. Nothing is uploaded — the index lives on the engagement team's hardware.
Synthesize themes across interviews, pull supporting quotes, and pressure-test the deck against the underlying data — with every answer cited.
Because nothing leaves the device, workflows align with clauses prohibiting third-party processing — no per-engagement DPA, no vendor cloud hop.
Inference, embeddings, and vector search run on the user's machine. No vendor data path to audit.
Every response links back to the exact source paragraph or row, so verification never means re-reading the binder.
Retrieval pulls only the relevant chunks per query — your index can be terabytes, not pages, with no per-token billing.
No. Most engagement letters prohibit sharing client data with third parties, including cloud AI vendors. PrivateDocs AI runs the entire RAG pipeline on the consultant's laptop — no document, prompt, or embedding leaves the device — so workflows align with those clauses by design.
Every answer links back to the source passage in the data room, interview note, or prior deliverable. Consultants can pull supporting quotes and verify themes against the underlying files without re-reading the whole binder.
After setup and activation, core inference and vector search can run offline. Confirm the parsing and update requirements for any restricted network before deployment.
Each consultant runs their own local vault on their own machine. There is no shared cloud index to misconfigure — the architecture itself enforces the per-engagement boundary. The vault is an exportable local folder, so it can be moved or archived under the client's data-handling terms.
$249 one-time license. No recurring fees. Document content stays local for AI processing.
Chat with supported data-room files — NDAs, purchase agreements, and disclosure schedules — without sending document content to a third-party AI cloud.
Layer 10-Ks, earnings commentary, and CSV data extracts into one analytical surface — with Chinese walls intact.
Summarize longitudinal notes, policy manuals, and reference PDFs where PHI must stay inside approved systems — not in a consumer chat product.
Query experiment logs, regulatory submissions, and internal memos without publishing trade-secret drafts to a hosted cloud assistant.