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Blake Technologies

AI architecture

Retrieval-augmented generation

Connect AI responses to selected business information through ingestion, access-aware retrieval, and source references.

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The answer is only as useful as the evidence behind it

Approved source collection

Procedure · version and owner
Policy · access rules
Reference · last reviewed date
Illustrative answer structure

Recommended next step

A concise response tied to retrieved evidence.

Supporting passage with a source reference

If evidence is missing or conflicting, explain the gap instead of filling it in.

Retrieval-augmented generation separates finding information from composing a response. Both need evaluation. An accurate-looking answer may still rely on an outdated or irrelevant passage, so source freshness and access rules are part of the design.

Diagnose the layer that failed

A retrieval and answer review
Observed problemInvestigate
The right document was never foundIngestion, chunking, filters, and search ranking
The source was correct but the answer was wrongPrompt behavior, evidence use, and answer evaluation
The answer crossed a permission boundaryAccess metadata and retrieval authorization
An old policy was returnedVersioning, deletion, and index refresh behavior
What should the first evaluation set contain?

Include ordinary questions, exact identifiers, ambiguous requests, missing answers, and requests for restricted information. Review both the retrieved sources and the final response.

Your project, scoped around the outcome

Build with Retrieval-augmented generation

Document ingestion, source-linked responses, and an evaluation dataset.

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