RAG Knowledge Base & Enterprise Search
Answers out of your own documents, with the source attached.
What is RAG Knowledge Base & Enterprise Search?
Your organisation already knows the answer. It's in a policy document, a contract, or a Confluence page somebody wrote in 2021 that nobody can find.
Retrieval-augmented generation fixes the finding problem. Ask in plain language, get an answer drawn from your own material, with a citation you can open and check. The citation is the point. An answer you can't verify is a rumour with good grammar.
Fair warning: this is where document quality becomes your problem. If three versions of a policy are live and contradict each other, RAG will cheerfully quote whichever it found first. We deal with that during the build, but it is work, and anyone telling you otherwise is selling.
Services provided
What the data says
The value isn't the model. It's the retrieval, the permissions and the citation. That's where these projects are won or lost.
Every RAG rollout doubles as a documentation audit. Expect to find contradictions nobody knew about.
Users forgive a slow answer. They don't forgive a confident wrong one with no source.
Related reading
- Technology & AI
RAG Done Right: Enterprise AI Search Without the Hallucinations
How to build enterprise AI search with RAG that staff trust: grounded, cited answers, permission-aware retrieval, evaluation and where to start.
- Digital Transformation
ERP at a Crossroads: Modernise the Core Without Stopping the Business
ERP modernisation succeeds or fails on decisions made before software selection. A practical guide to clean core, data, phasing and keeping trading.
- Digital Transformation
API-First Integration: Untangling Enterprise Spaghetti
An API-first integration strategy replaces point-to-point tangle with governed, reusable interfaces, and it is the prerequisite for AI agents that act.
Where Ganexa stands out
Citations aren't optional. If we can't attribute the answer, we don't show it.
We respect your permissions model from day one. Retrofitting access control onto a working index is miserable, and we'd rather not.
We'll tell you when your documents are the problem. Often the honest fix is deleting four of the six overlapping policies first.
It's plumbed into how documents are actually maintained, so it doesn't decay the week after launch.
Your engagement roadmap
Pick one question
1 weekWe choose a single high-volume question people keep asking, and find where the truth for it lives.
A scoped pilot, and a way to tell whether it worked.
Index and wire up
2–4 weeksIngest the sources, respect permissions, and get retrieval and citation working end to end.
A working pilot on your real content.
Let people break it
2 weeksReal users, real questions. We watch what fails and fix retrieval before widening scope.
Measured accuracy on questions that matter.
Widen
OngoingAdd sources, keep the index fresh, and track which questions still fall through.
A knowledge base that stays useful.
Built for where you are
Support and service desks
"Half our tickets are answered in a document the customer could never find."
Retrieval over your existing material, with the source shown so agents can verify before sending.
Fewer tickets, faster answers, and a trail back to the policy.
Policy-heavy organisations
"Nobody can find the current version of anything."
One place to ask, plus an unwelcome but useful map of everywhere your documents disagree.
The current answer, and a list of what to clean up.
Professional services firms
"The knowledge is in the heads of five people, and two of them are leaving."
We index what's written down and make plain what isn't, which is usually the bigger finding.
Less key-person risk.
What you walk away with
Working RAG pilot
On your real documents, with citation and permissions. Not a demo corpus.
Retrieval evaluation
Measured accuracy on the questions your people actually ask.
Permissions model
Access control enforced at retrieval, wired to your existing groups.
Document gap report
Where your sources contradict each other, or say nothing at all.
Freshness plumbing
Re-indexing tied to how the documents are really maintained.
Runbook
How to add sources and debug a bad answer, written for your team.
Ready to put RAG Knowledge Base & Enterprise Search to work?
Book a free 30-minute discovery call, you'll leave with a clear, costed next step, no obligation. Or ask us anything: we reply within one business day.
Questions we get asked about RAG Knowledge Base & Enterprise Search
What is retrieval-augmented generation?
A way of answering plain-language questions from your own documents. Every answer carries a citation you can open and check, which is what separates it from a chatbot guessing.
How long until we have something working?
Around five to seven weeks for a pilot on your real content: one week to scope a single high-volume question, two to four weeks to index and wire up retrieval, and two weeks of real users testing it.
Will it respect who is allowed to see what?
Yes. Permissions are enforced at retrieval from day one and wired to your existing groups, so people only see answers drawn from documents they can already access.
What happens if our documents contradict each other?
The build surfaces it. Every rollout doubles as a documentation audit, and you receive a gap report listing where sources disagree or say nothing at all.