AI Support Agent for a Fintech Company

How I built an AI agent that handles 75% of customer support tickets automatically — reducing L1 costs by 70% and response time from minutes to seconds.

How It Works

The AI agent sits between the customer and the support team, automatically resolving routine tickets and escalating complex cases with full context.

The AI agent handles incoming tickets in Freshdesk: analyzes content, pulls relevant information from the knowledge base, resolves straightforward requests, manages ticket statuses, and escalates edge cases to human operators with complete context attached.

The Problem

As the client's user base grew, so did support volume — linearly. 60-70% of tickets were repetitive questions that drained the team's capacity.

• Manual processing of routine requests slowed everything down
• Response quality varied depending on which operator answered
• Knowledge base existed but was underutilized
• Scaling meant hiring proportionally more staff
• Load spikes were unpredictable

Why a Simple Chatbot Doesn't Work in Fintech

The Solution: RAG-Based AI Agent

I built a Retrieval-Augmented Generation (RAG) agent — instead of relying on the model's training data, it retrieves verified information from a curated knowledge base before every response.

Think of it as a hyper-experienced librarian: understands the question, finds the right source, and formulates a precise answer following strict instructions.

• Consistent quality — every answer is grounded in verified sources
• Easy updates — change the knowledge base, not the model
• Fintech-compliant — sensitive data never leaves the system
• Security-first — customer PII is stripped before AI processing

Invisible AI

An interesting UX insight: users don't realize they're talking to an algorithm. At the client's request, we don't highlight the AI — preserving the familiar support experience and trust in the channel.

The pilot launch confirmed that users perceive conversations with the agent as talking to a human operator. The admin panel allows the team to update the knowledge base, adjust agent instructions, set temporary scenarios for incidents, and modify behavior — all without code changes.

Architecture for Scale

The system connects Telegram with Freshdesk into a unified workflow, supporting:

• Segmentation by user category (regular / VIP / enterprise)
• Routing by request type and complexity
• Multiple service levels with separate AI agents
• Dedicated agents for critical scenarios

Results

Technology Stack