Enterprise AI that keeps your knowledge private
InRag (Intranet RAG) is the most advanced and complete end-to-end solution for AI retrieval-augmented generation, ready to deploy. It answers questions from your organization’s own documents. Every answer quotes its source word for word, and sensitive data stays on your servers.
- On-premises or fully offline
- Secrets tokenized before any cloud LLM
- Every fact quoted word for word
- Ingest once, update only what changed
Why most organizations still can’t use AI on their own documents
Generative AI is ready. For organizations that hold sensitive data, the obstacles are trust, privacy and getting from a pilot to production.
Data leaves the building
Most AI assistants send your documents, including personal and financial details, to a cloud model you don’t control.
Answers you can’t verify
A fluent answer with no exact source is a liability. Staff can’t act on it, and auditors can’t check it.
Pilots that never ship
Assembling ingestion, search, models, access control and administration yourself takes months of engineering before anyone gets an answer.
Public AI wasn’t built for your organization’s documents
Public chatbots answer from what they learned on the internet, on someone else’s servers. Enterprise AI needs retrieval-augmented generation (RAG): AI that looks up the answer in your own documents, inside your own network.
Your data leaves your control
What staff paste into a public chatbot goes to a third party’s servers, where it may be stored or used to improve future models.
Knowledge frozen in time
A public model knows only what it learned before its training ended. It has never seen the policy you updated last week.
Training on your files is costly
Teaching a model your documents takes specialists and GPU time, starts over whenever documents change, and still can’t cite a source.
Faster answers. Lower costs. Less risk.
InRag turns the documents you already have into answers your staff can use and your auditors can check, without new hires or a long project.
Answers in seconds, not hours of searching
Staff ask in plain English and get the answer with its source attached, instead of digging through shared drives or waiting on a colleague.
No AI team, no per-question fees
One installer, one server and no code to write. With a local model there are no cloud fees per question, and updates reprocess only the files that changed.
Your data never leaves your control
Documents stay on your server, secrets are tokenized before any cloud model sees them, and every question and answer is logged for audit.
Answers you can check and defend
Every fact quotes your documents word for word, with a link to the page. When the answer isn’t there, InRag says so instead of guessing.
What is searching for information costing you?
The example below is for an organization of 5,000 employees. Move the sliders to match yours and see the time and money InRag could give back each year.
Starting example: 5,000 employees each spending 5 hours a week looking for information, at a fully loaded cost of $65 an hour, with 30% of that time saved. Based on 48 working weeks and 2,000 working hours a year. Your results will depend on your documents and how your staff work.
Better answers, by design
Most AI assistants bolt a chatbot onto a search index. InRag was engineered at every step, from reading a document to writing the answer, so the results are more accurate, more private and easier to trust.
The right passage, found the first time
InRag finds the passages that actually answer the question, so staff get complete, relevant results instead of scattered fragments.
Use the best AI models without exposing secrets
Social Security numbers, account numbers and salaries are swapped for placeholders before a cloud model sees them, then restored on your server.
No made-up answers
Every fact must quote your documents word for word. Unverifiable quotes are removed, and when the answer isn’t there, InRag says so.
Process your documents once. Ask as many questions as you like.
InRag reads and indexes your documents a single time. Every question after that is answered from the ready-made knowledge base in seconds, with no reprocessing. When documents change, InRag updates only what changed.
- Ingest once. Each document is read and indexed a single time.
- Unlimited questions. Every question searches the prepared knowledge base, so answers start in seconds.
- Scheduled updates. Daily, weekly or monthly schedules, plus a folder monitor that notices added, changed and deleted files.
- Only what changed. Unchanged files are skipped. A changed file is updated on its own, and a deleted file is removed from the knowledge base.
Only 4 documents were read again. Everything else in the knowledge base was left untouched, and the collection’s users were told what changed.
From installation to first answers in a single day
InRag is a finished product, not a toolkit. There’s no AI team to hire and no integration project to run: install it, point it at your folders, and your staff can start asking questions.
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Install
One installer sets up everything on your server, from a bare operating system to running services.
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Connect your folders
Choose the folders to read, group them into collections such as HR or Legal, and decide which departments can see each one.
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Build the knowledge base
InRag reads, OCRs and indexes your documents on its own. In our tests, about 380 business files were processed in roughly 5 minutes on one machine.
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Start asking
Staff sign up with their email and ask questions in the web chat or the Windows app, with answers quoted from your documents.
Everything included out of the box
- Web chat and a Windows desktop app for staff
- Admin console in the browser or on Windows
- User accounts with email sign-up and password reset
- Department-level access to collections
- Scheduled updates and folder monitoring
- Audit log of every question and answer
- Local or cloud language models, with privacy tokenization
- OCR for scanned documents
Skip the AI project. Keep the results.
Building a reliable, private RAG system means hiring specialists and assembling and maintaining a dozen moving parts. InRag gives you all of it, ready to run.
| Build it yourself | InRag | |
|---|---|---|
| People you need | Data engineers and AI specialists | Your existing IT staff |
| Parts to choose and connect | A dozen separate components, from document readers to AI models, accounts and apps | All included in one installer |
| Time to first answer | A development project | Day one |
| Protecting secrets from cloud LLMs | Design and build it yourself | Built in |
| Answers you can verify | Extra engineering | Every quote checked word for word |
| Keeping the knowledge base current | Custom software to write and run | Scheduled, only what changed |
| Access control and audit log | More to build | Included |
For enterprises and government agencies that can’t risk their data
InRag runs on a server you own, inside your network. Choose a local model and nothing leaves the machine at all, or use a cloud model with personal data tokenized first.
- On-premises deployment on Windows Server or Mac
- Fully offline operation with local language models
- Collections limited to a single department when needed
- Every question and answer logged for audit
See InRag on documents like yours
A live session with our team: questions, quoted answers, privacy tokenization and the admin console.
Request a Demo