Building an LLM-powered Quality Assurance System

At Deepmindz Innovations, we built an AI-driven quality assurance tool to automate call center evaluations — replacing manual scoring with real-time analytics powered by Large Language Models (LLMs).

Problem

Quality assurance teams in call centers spend hours listening to calls and manually filling evaluation forms. The objective was to automate this process with AI while maintaining high accuracy.

Solution

• Designed a FastAPI-based backend to handle streaming audio and text data
• Implemented Retrieval-Augmented Generation (RAG) for contextual accuracy
• Used LangChain and OpenAI models for semantic understanding of call transcripts
• Integrated PostgreSQL and caching for scalable data access

Impact

• Reduced evaluation time from 4 minutes to 8 seconds per call
• Achieved a 3× improvement in productivity
• Enabled consistent and explainable AI-based call scoring

This project proved how language models can augment enterprise workflows and deliver measurable business impact.