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Скачать или смотреть End-to-End AI project Using LangGraph + LangSmith + Azure Infra | Producton Grade Part 1 | Intro

  • AI with Chirantan
  • 2026-01-20
  • 93
End-to-End AI project Using LangGraph + LangSmith + Azure Infra | Producton Grade Part 1 | Intro
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Описание к видео End-to-End AI project Using LangGraph + LangSmith + Azure Infra | Producton Grade Part 1 | Intro

Welcome to the Production-Grade AI Series!

In this video, we are building "Brand Guardian"—an end-to-end AI agent that automates video compliance auditing. You will learn how to architect a Multi-Modal QA Pipeline that "watches" video ads, reads the on-screen text, listens to the audio, and cross-references everything against a legal rulebook using RAG (Retrieval Augmented Generation).

Instead of just building a chatbot, we are building a Workflow using LangGraph that orchestrates Azure's most powerful AI tools into a single, cohesive system.

🔥 What is the "Brand Guardian" Project? The Brand Guardian is an automated "AI Compliance Officer." In the real world, brands (like Nike, Coca-Cola, or Pharma companies) spend millions paying lawyers to watch hours of video content to ensure they aren't making false claims (e.g., "Guaranteed to work forever!") or missing required disclaimers (e.g., "Terms and conditions apply"). This project solves that problem. It takes a YouTube video URL, processes it using Azure Video Indexer, and uses GPT-4o to "judge" the content against strict PDF regulatory guidelines stored in Azure AI Search.

🛠️ Tech Stack & Tools Used:

Orchestration: LangGraph (Stateful Multi-Agent Workflows)

LLM Ops & Tracing: LangSmith (For debugging and optimizing prompts)

Video Intelligence: Azure Video Indexer (Transcript & OCR Extraction)

Knowledge Base: Azure AI Search (Vector Database for RAG)

LLM Brain: Azure OpenAI (GPT-4o)

Observability: Azure Application Insights (Production logs)

Storage: Azure Blob Storage

👇 What you'll learn in this high-level overview:

✔️ Architecture Design: How to design a Directed Acyclic Graph (DAG) for AI agents. ✔️ Multi-Modal Ingestion: How to extract text and visual data from video files using Azure. ✔️ RAG for Compliance: How to force an AI to strictly follow a "Rulebook" (PDFs) instead of hallucinating. ✔️ Production Tracing: Using LangSmith to see exactly what your AI is thinking. ✔️ System Health: Monitoring the pipeline with Azure Application Insights.

💡 Real-World Use Cases:

Influencer Marketing: Automatically audit thousands of influencer videos to ensure they say "#ad" or "Sponsored."

FinTech Compliance: Check financial advice videos for required risk warnings.

Pharma Ads: Ensure drug commercials list side effects as required by law.

Reach out to me :
LinkedIn :   / chirantanlonkar  
Github : https://github.com/SetuAI

#aiprogramming #ai #cloudcomputing #langgraph #langsmith #productiongrade #education #devops #cloudstorage

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