RAG-Based AI Search
Find trusted answers across thousands of documents in seconds.
The problem
Knowledge sits scattered across drives, wikis, tickets and databases. Finding the right answer means knowing where to look and trusting that it is current.
Retrieval-augmented search reads across those sources and answers in plain language — with citations back to the source, and only what each user is permitted to see.
What we build
- 01
Unified retrieval
Search that spans your documents, databases and knowledge bases, retrieving the passages that actually answer the question.
- 02
Source-backed answers
Responses that cite their sources inline, so a reader can verify every claim rather than take it on faith.
- 03
Permissions-aware access
Retrieval that respects existing access controls, so people only ever see what they are entitled to.
How it works
- 1
Index
Connect and index approved sources, preserving their permissions model.
- 2
Retrieve
For each question, fetch the most relevant passages the user is allowed to see.
- 3
Answer
Compose a grounded response with inline citations to the underlying documents.
- 4
Verify
Let the reader open any citation to confirm the answer against the source.
Where it applies
- Internal knowledge and policy search
- Customer and field support
- Research and analysis teams
- Compliance and legal reference
Have a complex problem worth solving?
Let's explore how AI and technology can move your organisation forward.