LLM Customer Support Agent System
Integrated custom OpenAI models and vector indexes with real-time slack triggers to automate inbound support inquiries.
The Challenge
Customer support desks were overwhelmed by thousands of basic repetitive support queries, increasing response times to over 12 hours.
Our Engineering Approach
Built a retrieval-augmented generation (RAG) system processing documentation databases through Pinecone and answering securely via Slack and web chat widgets.
Key Results & Business Impact
Successfully resolved 78% of incoming support requests autonomously, decreasing customer service response times down to under 5 minutes.
78% Tickets Automated
Operational metrics collected after 30 days of standard staging deployment.
Technology Stack
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