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# 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 β€” 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 β€” 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 β€” 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 β€” 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.