Entexis builds custom AI document assistants tailored to how your team actually reads: contract assistants, policy lookups, manual search, knowledge-base agents over your own files. Powered by retrieval-augmented generation (RAG) so every answer is grounded in your document with quoted passages. Multilingual out of the box (English, Hindi, Spanish, French & more). Works on documents in any major language. The tool below is a working example: drop a PDF, Word doc, or text file and ask questions. Try it. Then tell us what we should build for you.
This is a working showcase, not a SaaS product. The pipeline is real. We built it as an end-to-end example of what we ship to real clients. Drop any document; nothing is written to disk.
Typical outcomes when a business hires Entexis to build a custom AI document assistant (using retrieval-augmented generation, or RAG), drawn from real engagements. Numbers shift per use case, but the shape of the impact stays the same.
Every piece below was built end-to-end by the Entexis team. The same components (document ingestion, semantic search (embeddings), retrieval, grounded answers with citations) get re-tuned and re-shaped for your document types. (For the technical buyers: yes, this is a real RAG pipeline.)
The AI doesn't skim. It reads the whole file and finds the passage that answers your specific question, even when the wording differs.
Every answer comes from your document. The AI quotes the exact line(s) it used. If the answer isn't in there, it says so. It won't fabricate.
"What is the renewal clause?" "What is the total cost?" "Which section covers data retention?" Get a direct answer instead of skimming 80 pages.
The document is held in memory for an hour so you can ask follow-ups, then dropped automatically. Nothing written to disk; nothing logged. Custom builds support self-hosted models and zero data retention.
Drop in the file the team actually has. We extract the text automatically. Up to 8 MB. (Scanned image PDFs need OCR. A custom build adds it.)
For a real deployment we plug it into your contract repository, knowledge base, or wiki. Your auth, your storage, your model choice: including self-hosted Llama or Mistral if your data can't leave the building.
Documents in any major language: Hindi, Spanish, French, German, Arabic, Mandarin, Portuguese. Mixed-language repositories work too. Answers come back in your question's language.
Watch the answer come back with the exact lines from your document it used. The same retrieval-augmented generation (RAG) pattern that Entexis ships into production for client document stores, minus the engineering jargon.
PDF, Word, or plain text up to 8 MB. The AI reads it in seconds. No setup, no login.
The whole document gets prepared so the AI can find the parts that match a question, even when your wording differs from the document's.
The AI finds the parts of the document most relevant to your question and uses only those parts to answer.
The answer cites the exact lines used. Keep asking follow-ups. Your document stays loaded for an hour.
The demo above is one shape: drop a file, get grounded answers. We also build contract assistants, policy lookups, runbook agents, knowledge-base chatbots, and bespoke document AI (RAG) over your private repositories. Your model, your storage, your auth, your audit log. Two weeks for most builds.
We'll reply within one business day to talk about a RAG application tuned to your documents.
Hope that was helpful. Reach out anytime.