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.
AI Research and System Design · Relevance AI / Langflow · 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.
Delivered.
Intent routing agent
RAG policy answer flow
Structured data retrieval
Grounding and observability plan
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 built.
01
Audited the data sources, workflows, and constraints the system had to respect.
02
Designed the agent architecture: orchestration, state, grounding, and human checkpoints.
03
Built the pipelines, integrations, and evaluation harness around real cases.
04
Reviewed accuracy and failure modes, then documented the architecture for extension.
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