Help your team find answers in company documents, with sources they can check.
We connect your documents to a searchable knowledge service so people can ask questions and check the supporting sources. Access follows your document permissions. We test it against real questions and plan for documents being updated or removed.
- Searching across document stores
- Answers that are hard to verify
- Questions answered from your files
- Sources and permissions included
- Less time searching
- Answers with supporting sources
- Document access respected
Best for: Teams that need easier access to internal knowledge without losing document permissions
What you get
- Working knowledge service and document integrations
- Test questions, baseline results, and agreed quality targets
- Source citations, access controls, and update and deletion workflows
- Operating instructions and team handover
Scope & integrations
- Document ingestion and search on a managed service or custom system
- Source citations, document permissions, and update and deletion workflows
- Tests for finding relevant material and answering from it accurately
When this helps
- People spend too much time searching documents or asking colleagues for the same information.
- Your AI assistant gives answers that are difficult to verify against the original documents.
- A growing document collection has made search less useful, or raised questions about who can see what.
How the work happens
01Start with the questions people ask
Your subject experts help select real questions and the documents that answer them. We measure the current search or assistant against that set to establish a baseline.
02Compare the options
We assess managed services such as Bedrock Knowledge Bases, Azure AI Search, or Vertex AI, and custom options where needed. Results, access requirements, and running costs guide the recommendation.
03Connect documents and permissions
We build the ingestion and retrieval workflow with source citations and access checks. Updates, deletions, and permission changes follow an agreed schedule.
04Hand over the system and its tests
Your team gets the working service, results, and operating instructions. The tests stay with you so future changes to documents, search, or models can be checked.
Common questions
What do RAG and GraphRAG mean?
Retrieval-augmented generation (RAG) finds relevant material for an AI model to use in its answer. GraphRAG also uses relationships between entities or documents. We consider it when your questions need those connections and test whether the added complexity helps.
What accuracy can we expect?
We establish a baseline using your documents and questions, then agree targets in writing. We check both whether the right material is found and whether the answer is supported by it. The system can still make mistakes, so source checking remains useful.
Can people see documents they do not have permission to open?
The retrieval workflow is designed to check document access for the person asking. We test permission boundaries and agree how quickly permission changes and deletions need to reach the search index.