Claude is one of the strongest frontier models on the market for long-document reasoning — but every prompt, every uploaded file, and every Project still traverses Anthropic's cloud. For NDA-bound, HIPAA, attorney work-product, or client-confidential material, that vendor cloud hop is the blocker. PrivateDocs AI runs the same 'chat with your documents' workflow entirely on your hardware, with per-message citations back to source.
Compared to: Claude Pro · Claude Team · Claude Enterprise · Claude Projects · Anthropic API
PrivateDocs AI vs. Claude Pro, Claude Team, and Claude Enterprise for confidential document workflows
| Feature | PrivateDocs AI | Claude (Anthropic) |
|---|---|---|
| Where prompts and documents are processed | On-device document and AI processing | Sent to Anthropic cloud infrastructure |
| DPA & subprocessor review | Not required for AI workloads | Mandatory Anthropic DPA + tenant setup |
| Training on your data | Impossible — we never see your data | Disabled by policy, but still processed in cloud Claude Enterprise opts you out of training, but content still passes through Anthropic servers for inference. |
| Context window vs. local vault | Local retrieval across supported files; practical size depends on hardware | 200K-token window per request (Projects) Claude Projects cap grounding at a single context window. PrivateDocs AI retrieves relevant chunks per query, while practical corpus size depends on your storage, memory, and model capacity. |
| Air-gapped operation | Full local inference after activation | Requires active internet connection |
| Vector store & document retention | Local ChromaDB vault on your disk | Hosted in your Anthropic workspace |
| Citations to source documents | Citations can link to retrieved source passages | Requires custom prompting / Projects setup |
| Pricing | $249 one-time lifetime license | $20–$60+/user/month, recurring |
For 'chat with your own documents' workflows, yes. PrivateDocs AI uses modern open-source LLMs (Llama 3, DeepSeek, Mistral) through a bundled Ollama runtime, indexes your files in a local ChromaDB vault, and generates per-message citations. The quality is comparable on document Q&A and summarization — and the privacy posture is fundamentally stronger because no document or prompt ever leaves your machine.
Claude Projects let you pin reference material, but everything still routes through Anthropic's cloud and is bounded by the model's context window. If your client contract, NDA, or regulatory posture prohibits that egress, Projects don't help. PrivateDocs AI gives you the same conversational document workflow with zero egress and an effectively unlimited corpus via local vector retrieval.
For short documents, a long-context model is a great UX. At larger scale, retrieval can select relevant chunks from a local index rather than loading the entire corpus into one context window. Practical size and citation behavior depend on the files, model, and hardware.
Many teams do exactly that. Claude is excellent for general reasoning, writing, and code; PrivateDocs AI is the right tool the moment a document is covered by an NDA, attorney work-product privilege, HIPAA, GDPR, or any clause that prohibits third-party processing.
$249 one-time license. No recurring fees. Document content stays local for AI processing.
PrivateDocs AI vs. Ollama — Production-ready RAG vs. raw model runtime
PrivateDocs AI vs. self-hosted AnythingLLM, LangChain, and LlamaIndex setups
PrivateDocs AI vs. ChatGPT, Claude, Gemini, and Copilot for confidential documents
PrivateDocs AI vs. hosted enterprise RAG portals and tenant AI subscriptions