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.
Type: AI Research and System DesignStack: Relevance AI / LangflowMarket: Academic / Internal
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.
Visual Proof
A designed view of the system Avlys delivered.
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Detail View
03
Core
Workflow View
04
Core
Scope
What was delivered.
01
Intent routing agent
02
RAG policy answer flow
03
Structured data retrieval
04
Grounding and observability plan
Process
Step 01
Mapped the user journey, operating workflow, and conversion or handoff points.
Step 02
Defined the information architecture, system rules, and implementation plan.
Step 03
Built the interface, integration layer, content structure, and launch-ready handoff.
Step 04
Reviewed performance, responsiveness, QA issues, and post-launch support needs.
Outcomes
Outcome 01
A clearer support automation architecture for ecommerce use cases.
Outcome 02
Reduced risk of unsupported answers through grounding.
Outcome 03
Defined agent roles for routing, retrieval, and response.
Outcome 04
A research-backed base for support automation implementation.
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