Company: TCS
Role: Full Stack AI Engineering
Project: DNB (Enterprise Banking)
About Project:
I designed & developed DNB CENTRIX, an AI Agent-enabled enterprise incident management and developer assistance platform that leverages Hybrid RAG architecture to provide intelligent debugging, issue resolution, and automated incident routing. I leverages a Hybrid RAG architecture to provide intelligent debugging, issue resolution, and automated incident routing for developers.
Key Technical Works:
- Built an AI-powered incident resolution assistant that enables developers to query, analyze, and resolve production issues using natural language.
- Designed a Hybrid RAG architecture (combining vector and non-vector retrieval) that integrates Confluence documentation, internal portals, and source code repositories.
- Implemented AI agents for incident triage and resolution recommendation, giving them the capability to analyze logs, error patterns, and historical fixes.
- Developed an intelligent ticket routing system where AI agents autonomously assign incidents to the most suitable developer based on skill matching and past resolution history.
- Integrated enterprise knowledge sources (Confluence, internal documentation, code repositories) into a unified semantic search system.
- Designed an LLM-based reasoning layer to provide root cause analysis and step-by-step debugging suggestions.
- Built a secure API-driven microservices architecture using FastAPI and managed containerized deployments with Docker and Kubernetes.
- Implemented RAG optimization strategies to improve retrieval accuracy and reduce hallucinations in technical responses.
- Enabled significant developer productivity improvements by reducing incident diagnosis time and increasing resolution accuracy through AI assistance.
Skill Sets:
Python, Hybrid RAG Architecture, AI Agents, Semantic Search, LLM Reasoning, FastAPI, REST APIs, Microservices Architecture, Docker, Kubernetes.