Context
The system explored how an ecommerce support flow could use multiple agents to route requests, answer policy questions, and retrieve structured data.
AI & Agentic Systems
Multi-Agent Customer Support System
A three-agent support system design for routing, retrieval, and structured customer answers.
Architecture engagement · AI Research and System Design · Relevance AI / Langflow
Project illustration. Not a verified production screenshot.
Engagement: Architecture engagement. Architecture and design scope; this is not a claim of a live production deployment.
The capabilities below describe the work delivered. Quantified business results have not been published.
Challenge
Support automation needs grounding and observability. The design needed to avoid generic answers by separating routing, policy retrieval, data lookup, and monitoring.
Solution
Avlys designed a three-agent support system with Relevance AI and Langflow patterns, including routing, RAG policy answers, structured data retrieval, grounding, and observability research.
Delivered.
Intent routing agent
RAG policy answer flow
Structured data retrieval
Grounding and observability plan
Design outcomes.
A clearer support automation architecture for ecommerce use cases.
Reduced risk of unsupported answers through grounding.
Defined agent roles for routing, retrieval, and response.
A research-backed base for support automation implementation.
How it was designed.
01
Mapped request types and support knowledge sources.
02
Separated intent routing, policy retrieval, and structured data lookup.
03
Specified grounding and observability requirements.
04
Documented the proposed support architecture for implementation.
Related work.
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