# Video Compliance AI

Video Compliance AI is an agentic system that automatically audits YouTube videos for FTC regulatory compliance. Give it a YouTube URL and it returns a structured audit report detailing any violations found — missing disclosures like #ad or #sponsored, misleading claims, and unsubstantiated endorsements. No human needs to watch the video.

## What It Does

Brand teams and agencies manually review influencer videos for regulatory compliance — slow, inconsistent, and expensive. This system automates the full pipeline: download the video, extract speech and on-screen text, retrieve relevant FTC rules, reason over the evidence, and return a structured JSON audit report.

## How It Works

Azure Video Indexer downloads the video via yt-dlp and simultaneously performs speech-to-text transcription and OCR on on-screen text. This multimodal ingestion captures both spoken claims and text overlays. The transcript and OCR output are combined into a query that retrieves the top 3 relevant FTC rule chunks from Azure AI Search, which holds the FTC Disclosures guide and YouTube Ad Specifications as indexed vectors. GPT-4 then reasons over the video content against those retrieved rules and returns a structured compliance verdict.

The entire pipeline is orchestrated by a two-node LangGraph DAG — an indexer node handles ingestion and an auditor node handles RAG reasoning. Both nodes share a TypedDict state object.

## What Makes It Interesting

The system is deployed as a production FastAPI service with Azure Monitor and OpenTelemetry auto-instrumentation capturing request latency, error rates, and dependency traces. LangSmith provides per-node agent trace inspection for debugging. Authentication uses DefaultAzureCredential — in development it uses Azure CLI, in production it switches automatically to Managed Identity with no code change.

## Tech Stack

Python, LangGraph, LangSmith, Azure Video Indexer, Azure AI Search, Azure OpenAI (GPT-4), Azure Monitor, OpenTelemetry, FastAPI, Pydantic, yt-dlp.