We Built an AI Support Agent That Resolves 80% of Tickets — AssemblyAI
Matt Lawler of AssemblyAI details the creation of 'Joey,' an advanced AI support agent designed to solve the scaling bottleneck inherent in the Forward Deployed Engineer (FDE) model. Faced with 1,000 API signups daily and limited human resources, the team replaced an ineffective off-the-shelf bot (10% resolution) with Joey. Joey, built on the Claude Agent SDK, achieves an 80% end-to-end resolution rate for approximately $700/month. The architecture leverages local markdown documentation, external embeddings, agentic file search, and a large `CLAUDE.md` system prompt. The agent's capabilities were further enhanced by integrating AssemblyAI's Voice Agent API, allowing for real-time, low-latency voice interactions.
Key takeaways
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Scaling the FDE Model
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The FDE model, while effective for building trust, does not scale to handle high volume (e.g., 1,000 API signups/day). Automation is necessary to maintain a high-quality customer experience at scale.
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Agentic Architecture Improvement
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Joey was built to overcome limitations of vendor bots by giving the agent full control over its infrastructure, including file system access, tool calling, and the ability to write/debug code.
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Performance Gains
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The agent increased the end-to-end resolution rate from 10% to 80% in the first week of deployment, costing around $700/month.
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Voice Integration
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The agent was given a voice interface using the Voice Agent API, which strings together speech-to-text, LLM, and text-to-speech over a single websocket connection for real-time, low-latency interaction.