End To End Multimodal LLMOPS Project Azure Deployment With Observability And Orchestration Engine

Description

This project establishes an automated Video Compliance QA Pipeline orchestrated by LangGraph, designed to audit content against regulatory standards using a RAG architecture. We leverage Azure Video Indexer for multimodal ingestion (transcripts/OCR) and Azure AI Search to retrieve relevant compliance rules via Azure OpenAI Embeddings. The core reasoning engine, Azure OpenAI (GPT-4o), synthesizes this data to deterministically detect violations, while LangSmith provides granular tracing for LLM workflow optimization. Additionally, Azure Application Insights is integrated for production-grade telemetry, logging, and real-time performance monitoring. This end-to-end system transforms unstructured video into structured, actionable JSON compliance reports with deep full-stack observability. Code: https://drive.google.com/drive/folders/12YEfALjwaIrigSbPfNo6qeQKG1alHo56 Mentor: Chirantan : https://www.linkedin.com/in/chirantanlonkar/ Join our Industry Ready Projects: https://www.krishnaik.in/projects