Enterprise Questionnaire Intelligence Platform
An illustrative multi-agent system for turning enterprise evidence into source-grounded questionnaire responses with human oversight.
6 min explorationExplore the thinking
Multi-Agent RAG Architecture
A reference design that separates experience, orchestration, agents, evidence and governance so a generated answer can be inspected.
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
- A plausible answer is difficult to trust when retrieval, reasoning and approval are hidden inside one opaque workflow.
- Approach
- Define explicit component boundaries, evidence contracts and a review path across the architecture.
- Outcome
- Intended outcome: An inspectable system with clear evidence lineage and accountable release decisions. 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.
Follow the evidence through the system
Select a component to see its purpose, inputs, outputs, candidate technologies and connected components.
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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
Retrieval quality, source permissions, answer quality and review authority are different concerns. Combining them without clear boundaries makes failures difficult to isolate.
Design principles
- Specify evidence contracts before choosing an agent framework.
- Keep authorization attached to retrieval.
- Make unsupported answers observable and recoverable.
Component contracts
The experience submits an authorized task. Orchestration maintains state. Agents consume scoped evidence; the knowledge layer retains provenance. Governance captures decisions across the flow.
Key decisions
The diagram shows a candidate decomposition rather than a required technology stack. A simpler single-agent workflow may be preferable when the task does not justify orchestration.
Governance
Evaluate access-aware retrieval, tool permissions, evaluation coverage and release ownership as separate controls. Logging must support investigation without indiscriminately copying sensitive source content.
Implementation considerations
Test document segmentation, retrieval coverage, stale evidence, conflicting sources and failure recovery before introducing additional agents.
Business impact
The intended benefit is more reproducible review and clearer failure diagnosis. Actual performance, costs and business impact remain to be documented.