LLM-Powered Support Agent

An AI customer support agent that resolves 78% of tickets without human intervention — trained on the client's knowledge base and fine-tuned to match their brand voice exactly.

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The Challenge

Our client — a mid-size e-commerce company — was drowning in support tickets. Their 12-person support team was spending 60% of their time answering the same 200 questions repeatedly. Customer wait times averaged 4 hours, and satisfaction scores were declining.

They needed an AI solution that could handle their full knowledge base, maintain their brand's conversational tone, escalate complex issues intelligently, and integrate seamlessly with their existing Zendesk setup.

Our Solution

We built a Retrieval-Augmented Generation (RAG) pipeline using Claude as the foundation model, with a custom vector database (Pinecone) indexing their entire knowledge base, 3 years of resolved tickets, and product documentation. The agent handles context switching, multi-turn conversations, and ambiguous queries with human-level accuracy.

A confidence-scoring system routes uncertain queries directly to human agents with full conversation context — so agents pick up exactly where the AI left off, with zero customer friction.

Technology Stack

Claude API (Anthropic) LangChain Pinecone Python FastAPI Zendesk API Redis AWS Lambda OpenAI Embeddings

Outcomes

Results & Impact

78%

Tickets resolved without human agents

4h → 2min

Average first response time

41%

Reduction in support team workload

Build With Us

Ready to automate
your customer support?

We can build and deploy a custom AI support agent for your business in 4–6 weeks. Let's talk.