Multi-Agent RAG Architecture
A reference design that separates experience, orchestration, agents, evidence and governance so a generated answer can be inspected.
6 min explorationExplore the thinking
Enterprise Questionnaire Intelligence Platform
An illustrative multi-agent system for turning enterprise evidence into source-grounded questionnaire responses with human oversight.
Illustrative sample designconcept · 6 min exploration
Illustrative sample content. Source material and role attribution are pending; this is not a claim of delivery or measured results.
- Problem
- Enterprise questionnaires require repetitive evidence discovery while each answer may create a material commitment.
- Approach
- Separate retrieval, evidence evaluation, drafting and validation; place approval with a named human reviewer.
- Outcome
- Intended outcome: Less repetitive analysis, more consistent answers and a traceable path from source to response. No measured results supplied.
- My role
- Attribution pending. Personal, leadership and collaborative contributions will be specified when the source artifact is supplied.
THE DESIGN IN DETAIL
How it works.
From question to accountable answer
Select an agent to inspect its objective, evidence, tools and human checkpoint. The connections show proposed handoffs.
Loading the interactive design…
Go deeper into the assumptions, decisions and controls.
Context
Illustrative design only. This sample is not a record of a deployed system, a completed engagement, or measured results.
Problem
Finding an answer is only part of the task. A reviewer also needs to know what supports it, whether the evidence is current, and who can authorize the response.
Design principles
- Keep source evidence attached to every proposed answer.
- Treat missing evidence as a gap rather than an invitation to guess.
- Separate drafting permission from approval authority.
Architecture & workflow
The sample routes work through specialized agents. A shared evidence package preserves source references, coverage gaps and workflow state. Validation prepares the draft for human review; it does not replace that review.
Key decisions
Prefer bounded responsibilities over one unconstrained agent. Preserve an explicit unknown state when sources cannot answer a question. Keep the release decision outside the generation step.
Governance
A source access boundary, reviewer ownership and a decision record are proposed controls. Exact access policies, retention periods and validation criteria require the actual implementation context.
Implementation considerations
Source freshness, document permissions and reviewer workload must be evaluated before selecting tools. No deployed technology stack is asserted by this sample.
Business impact & measurement
A future case study should distinguish time spent finding evidence, time spent reviewing answers and the rate of unsupported drafts. No baseline or numeric improvement has been supplied.
Questions to validate
Can a reviewer reproduce the evidence trail? Can the workflow stop without a confident answer? These are design questions for the future artifact, not claimed lessons from a deployment.