IP Detection at Scale: CI/CD Meets Cloud-Native Enforcement
summary
A production pipeline that ingests millions of listings per day and uses multimodal embeddings with ANN via AWS OpenSearch performs subsecond P99 lookups at massive scale; index versioning and immutable event streams enable instant rollbacks and replay. Orchestration runs on Amazon Kinesis, SNS/SQS and Step Functions with circuit breakers. The hybrid flow uses fine‑tuned YOLO V7, Roberta and domain adapted bird models, plus LLM‑assisted verification, yielding 78% autoverification and a 68% reduction in manual review while doubling throughput and halving P99 latency.
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chapters (12)
- 0:00Introduction and Overview
- 0:46The Challenge of IP Violations at Scale
- 2:01Limitations of Traditional Approaches
- 3:28Core Philosophy: Production ML as a Systems Problem
- 4:21High-Level System Architecture
- 5:39Technical Stack and Detection Workflow
- 8:26Confidence-Based Enforcement Strategy
- 10:11CICD and Model Governance
- 11:08Observability and Monitoring
- 12:01Incident Response and Debugging
- 13:37Results and Operational Impact
- 14:16Conclusion
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