AI-Powered Customer Support Platform

The client's support team was handling over 12,000 tickets per month across email, chat, and in-app messaging. With a lean team of 15 agents, response times averaged 8+ hours during peak periods, and first-contact resolution was stuck at 38%. Hiring more agents wasn't sustainable — support costs were already eating into margins, and the company needed a solution that could scale without linear headcount growth.

The bigger problem: existing off-the-shelf chatbot solutions failed. They couldn't understand the nuance of technical product questions, gave generic answers, and frustrated customers more than they helped. What the client needed was a custom AI system trained specifically on their product, documentation, and historical ticket data.

We built a three-layer AI support platform:

• Layer 1 — Intelligent Triage: A classification model routes incoming tickets by intent, urgency, and customer tier. Simple queries go straight to the AI; complex ones route to specialized human agents.
• Layer 2 — LLM-Powered Resolution: A fine-tuned LLM, augmented with a RAG pipeline built on the client's documentation, past resolutions, and knowledge base, generates accurate, context-aware answers. It cites sources and admits when it doesn't know.
• Layer 3 — Seamless Escalation: When confidence is low or the customer requests a human, the AI hands off to an agent with full conversation context and suggested responses — no repeat questions, no lost context.

We also built an admin dashboard with real-time analytics, ticket quality scoring, and continuous learning loops — so the AI gets smarter as it handles more conversations.

Within 90 days of launch, the platform delivered measurable results: