Solution
RAG Knowledge Assistant for Business Documents
An AI assistant that answers from your own business documents, with the source shown.
The situation
The answer exists somewhere in the policy manual, the matter file or last year's proposal. Finding it costs more than reading it.
What the system takes over
- Indexing your documents into a searchable knowledge base
- Answering questions in plain language, grounded in those documents
- Showing the passages each answer came from
- Declining to answer when the documents do not cover it
How a run goes
Four steps, and the last one is a person.
- 01
Ingest
Your documents are indexed with access rules carried over.
- 02
Retrieve
The relevant passages are found for each question.
- 03
Answer
The answer is written from those passages only, with citations.
- 04
Verify
You can open the source for any claim before relying on it.
Where a person stays in chargeAnswers cite their source passages. When nothing relevant exists, the assistant says so rather than inventing one.
Built with
The tools involved.
In delivered work — appears in something that shippedCompatible — the system can connect to it; scoped per project, no track record claimed
- ClaudeIn delivered work
- OpenAIIn delivered work
- SupabaseIn delivered work
- PostgreSQLIn delivered work
- GeminiIn delivered work
- NotionIn delivered work
- SlackCompatible
Questions
What people ask first.
- Does our data train a public model?
- Data handling is scoped in the audit and described on the Security page. The architecture is built so your documents are not used to train shared models.
- How do you stop it making things up?
- Answers are limited to retrieved passages and must cite them. If retrieval comes back empty, the answer is that it does not know.
Next solution: CRM & client operations
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