AI Knowledge Assistant (RAG)
End-to-end build: document ingestion, search, AI answers, and the web interface your team actually uses.
Enterprise AI Search & Knowledge Assistants
Turn your company's documents into instant, trustworthy answers
We build private AI search assistants that answer staff questions from your own policies, manuals, and data. Every answer cites its source, and nobody sees information they aren't authorised to see.
The problem
Your knowledge is scattered, and public AI doesn't know your business
Your knowledge is spread across PDFs, shared drives, wikis, and inboxes. Employees waste hours searching, ask colleagues the same questions, or act on outdated information. Public AI chatbots don't know your business, and they can make things up with confidence.
What we build
A secure AI search system built on your own documents
Enterprise AI Search & Knowledge Assistants: a secure system, hosted in your environment or ours, that does the following.
Plain-language answers with citations
Answers questions from your documents, with citations to the exact document and page.
Says "I don't know"
When your documents don't contain the answer, it says so instead of guessing.
Respects permissions
HR files stay with HR, finance with finance, and each client's data stays separate.
Understands meaning and exact terms
Finds "password requirements" when someone asks "how long should my password be?", and also exact codes, product numbers, and names.
Connects to live sources
News feeds, status pages, and approved APIs, labelled with what's current and when it was last checked.
Flags contradictions
Catches conflicts between documents — an old policy versus a new one, for example.
Resists manipulation
Instructions hidden inside documents can't hijack the assistant.
Measures its own accuracy
Automated quality tests, so you see results rather than promises.
Use cases
One assistant, every team
HR & Operations
"How many leave days do new hires get?" — answered from the current handbook.
Customer Support
Agents find troubleshooting steps from product manuals in seconds.
IT & Security
Search runbooks, incident reports, and security policies instantly.
Legal & Compliance
Compare requirements across contracts and regulations, with page references.
Management
Query reports and operational documents without digging through folders.
Our services
What's included
Enterprise search API
A search engine your existing tools and apps can call directly, instead of a standalone destination.
Data connectors
Integrations with RSS feeds, public and internal APIs, and document repositories you already use.
Security & access control
Single-tenant or multi-tenant setups, role-based permissions, and full audit logs.
AI quality evaluation
Test sets and dashboards that measure accuracy, citation correctness, and data leakage — on an ongoing basis.
Deployment & support
Docker-based deployment on your cloud or servers, monitoring, backups, and ongoing improvement.
How we work
From discovery to a measured production rollout
STEP 01
Discovery (1–2 weeks)
We review your documents, users, permissions, and success criteria.
STEP 02
Proof of concept (2–4 weeks)
A working assistant on a sample of your real documents, with measured accuracy.
STEP 03
Production build
Security hardening, integrations, user interface, and deployment.
STEP 04
Launch & improve
Monitoring, user feedback, and regular quality evaluations.
Security & privacy
Your data stays yours
Your environment, your cloud
Deploy in your own cloud or on-premises: your data never has to leave your environment.
Your choice of model
Works with OpenAI, Anthropic Claude, or fully private open-source models that run on your own hardware, with no data sent to third parties.
Permissions enforced upfront
Access checks happen before any information reaches the AI, not after.
Full audit trail
Every login, upload, download, and permission change is logged.
Encryption & retention controls
Encryption, secure authentication, and configurable data retention.
Proof: see it working
A complete reference platform, already built
We've built a complete reference platform that demonstrates all of the above. In our internal evaluation on sample public-domain documents, it found every expected document, cited every source correctly, and leaked nothing across permission tests — in about 60 milliseconds per response.
Demo results on our test dataset. Results for your organisation depend on your documents and chosen AI model, and we measure them during the proof of concept.
Reference-platform evaluation on sample public-domain documents: every expected document found, every citation matched, zero permission leaks.
100%
Expected documents found by search
100%
Citations matched real retrieved sources
0
Permission leaks across security tests
~60ms
Typical search response time
Technology
Built on a proven, production-grade stack
FAQ
Common questions about enterprise AI search
Will the AI make things up?
It answers only from your documents and cites every claim. When the documents don't contain an answer, it says so instead of guessing. Every citation can be checked against the exact source document and page.
Can it use our existing documents?
Yes — PDF, Word, text, and web pages, including scanned documents through OCR. It connects to the documents, drives, and wikis you already have rather than requiring you to re-enter everything into a new system.
Do we need to send our data to OpenAI?
No. We can run fully private open-source models entirely inside your own infrastructure, with no data sent to third parties. You can also choose OpenAI or Anthropic Claude if that fits your setup better — the choice is yours.
How long does it take?
A working proof of concept typically takes 2–4 weeks, built and measured against a sample of your real documents. A full production rollout depends on your integrations and security requirements, scoped after the proof of concept.