Building an AI-Assisted Chat Support System
A tiered chat flow that resolves common customer queries automatically and routes the rest to the right human department, with context carried between conversations.
The problem
A client needed a support system that could handle high volumes of customer queries without forcing every conversation through a live agent — but customers still needed a fast path to a real human when the situation called for it.
The approach
I built a tiered chat flow. Every conversation starts with a bot that verifies the user before anything else. Once verified, the user moves into an AI-assisted chatbot that handles common queries directly — order tracking, order status, and general information about the company's offerings — pulling from structured data rather than guessing.
If the query goes beyond what the bot can resolve, the system detects intent and guides the user step-by-step into a handoff, routing them to the correct department instead of a generic queue. The bot also maintains context from the user's last conversation, so returning users don't have to re-explain themselves.
Stack
Laravel, AI/LLM integration, real-time messaging (WebSockets), OpenAI API, custom bot logic, structured data handling, secure user verification, embedding, and context management.
Outcome
Reduced load on live support agents by resolving common queries automatically, while preserving a fast, accurate path to human support when needed.
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