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AI assistants · Knowledge systems

More grounded answers from business knowledge.

A conversational system combining retrieval, persistent context and specialist agents that propose, review and refine responses.

Illustrated overview of the ai assistants workflow

01 / THE CHALLENGE

The work that needed to change.

A single response step can lose conversation context or produce answers without enough supporting information. The system needed a clearer separation between retrieval, reasoning and review.

02 / THE SOLUTION

Connecting the right steps.

Modular workflows retrieve relevant evidence and preserve session context. A proposer prepares an answer, a critic reviews it, and a synthesiser assembles the final response with output checks.

  • Retrieval-augmented generation
  • Session memory and file context
  • Separate proposer, critic and synthesiser workflows
  • Context filtering and output validation

03 / THE WORKFLOW

How the system works.

  1. 01Receive a question
  2. 02Check the input
  3. 03Retrieve & rank context
  4. 04Propose an answer
  5. 05Review & refine
  6. 06Validate the response

04 / THE OUTCOMES

What the workflow made possible.

  • Made conversation context persistent across requests.
  • Separated responsibilities into maintainable components.
  • Added evidence retrieval and response review to the answer process.

05 / TECHNOLOGY

Tools behind the workflow.

n8nSupabasePostgreSQLGeminiClaudeLangChain

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