CASE STUDY

AI Voice Agent Platform

Automating high-volume FinTech support with ultra-low latency conversational AI and secure ledger integration.

01 — THE CHALLENGE

The Problem

A rapidly scaling European FinTech enterprise was experiencing an unsustainable surge in tier-1 customer support calls. Their existing IVR (Interactive Voice Response) system was rigid, frustrating to users, and incapable of resolving complex inquiries without human intervention.

During peak trading hours, average wait times exceeded 15 minutes, leading to severe customer dissatisfaction and high abandonment rates. The client required a sophisticated, human-like AI voice agent capable of authenticating users, securely retrieving account balances, and executing basic transactions without requiring a live agent.

02 — OUR APPROACH

The Architecture

We architected an event-driven, serverless pipeline utilizing Twilio Voice APIs deeply integrated with a custom Retrieval-Augmented Generation (RAG) system.

When a call is initiated, Twilio streams the audio to Google Cloud Speech-to-Text (STT) for instantaneous transcription. The text payload is routed via AWS API Gateway to a Lambda function, which acts as the orchestrator. The Lambda queries a locally hosted, fine-tuned LLaMA-based model to determine user intent.

If account data is required, the orchestrator triggers secure, internal API calls to the bank's core ledger. The generated response is passed to Deepgram’s highly realistic Text-to-Speech (TTS) engine, returning the audio stream back to the user via Twilio. The entire round-trip latency (STT ➔ LLM ➔ TTS) was optimized to under 800 milliseconds, ensuring a fluid, conversational cadence.

03 — TOOLS & TECHNOLOGIES

Technology Stack

Twilio Voice API
Python / FastAPI
AWS Lambda Serverless
Google Cloud STT
Deepgram TTS
Custom LLaMA 3 Model
Redis (State Cache)
04 — RESULTS

The Outcome

Successfully automated 60% of all tier-1 support calls within the first month of deployment. Average user wait times dropped from 15 minutes to literally 0 seconds. Call center operating costs were reduced by 45%, allowing human agents to focus exclusively on high-value, complex dispute resolutions.
READY TO START?

Want similar results?

Let's discuss your project — we'll build the right solution together.