ContentGuard™ AI - Intelligent Piracy Network Dismantling System
Deploys a multi-agent AI orchestration system that autonomously scans platforms, fingerprints content using neural embeddings, maps piracy networks through graph analysis, and executes automated DMCA enforcement with high success rates..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Mission Control Center for configuring AI-powered content protection with content assets, target platforms, and multi-agent system architecture
Real-time AI agent orchestration dashboard showing multi-agent execution, chain-of-thought reasoning, and tool execution logs
Network Intelligence graph analysis using Neo4j to visualize piracy networks with Cypher queries and identified threat clusters
Mission completion summary displaying detection results, enforcement metrics, revenue protection, and 7-phase workflow execution timeline
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Complex multi-agent workflows require intelligent coordination to delegate tasks, monitor execution, and adapt strategies based on real-time results across heterogeneous agent capabilities.
Core Logic
Powered by Claude Sonnet 4.5 with RAG-enhanced planning, coordinates all agents through task delegation, execution monitoring, and workflow management. Maintains shared context across agents, handles error recovery, and optimizes resource allocation. Uses specialized tools including task delegation and progress monitoring.
Content Scanner Agent
Pirated content appears in modified forms across platforms—compressed, re-encoded, cropped, or altered—making traditional hash-matching ineffective for detection at scale.
Core Logic
Uses GPT-4o for multi-modal content fingerprinting with neural embeddings. Employs Perceptual Hash, Chromaprint audio fingerprinting, and deep learning embeddings to detect content regardless of alterations. Scans across multiple platforms simultaneously with specialized tools for fingerprint matching and platform scanning.
Pattern Analyzer Agent
Organized piracy operations exhibit coordinated upload patterns, timing anomalies, and behavioral signatures that individual infringement analysis fails to detect.
Core Logic
Leverages Claude Sonnet 4 with ML anomaly models including Isolation Forest, Autoencoder, and Local Outlier Factor. Performs velocity analysis on upload timing, detects coordinated behavior across accounts, and identifies operational patterns. RAG-enabled with pattern knowledge base.
Network Mapper Agent
Piracy networks span multiple entities—uploaders, domains, hosting providers, payment processors—with hidden relationships that require graph analysis to expose.
Core Logic
Employs Claude Sonnet 4.5 for graph-based network analysis with GNN embeddings. Applies PageRank for hub identification, Louvain and Girvan-Newman algorithms for community detection. Maps entities and relationships into clusters using graph traversal and community detection tools.
Enforcement Agent
Manual DMCA and DSA compliance processes are slow, error-prone, and fail to package evidence in legally admissible formats required for platform takedowns and legal proceedings.
Core Logic
GPT-4o powered agent with legal RAG for automated DMCA/DSA compliance. Packages evidence with cryptographic hashing for legal admissibility, verifies legal basis for each takedown, and submits to platform APIs. Tracks success rates per platform using DMCA submission and evidence packaging tools.
Intelligence Reporter Agent
Stakeholders across executive, technical, and business functions require different report formats and depth levels from the same underlying detection and enforcement data.
Core Logic
Claude Sonnet 4 agent generating multi-format reports with data visualization. Produces executive summaries with KPIs, technical reports with algorithm metrics and network topology, and business analyst reports with workflow breakdowns using specialized report generation tools.
Continuous Monitor Agent
Piracy networks quickly re-upload content after takedowns, requiring persistent surveillance to detect reappearance and measure long-term enforcement effectiveness.
Core Logic
Gemini 2.0 Flash powered for real-time surveillance with predictive reappearance modeling. Monitors post-mission, tracks view velocity and revenue impact, generates alerts for new infringements using reappearance detection and alerting tools.
Predictive Intelligence Agent
Reactive enforcement cannot prevent infringement during critical release windows when content value is highest. Proactive threat forecasting is essential for premium content protection.
Core Logic
Claude Sonnet 4.5 with ML prediction models for infringement forecasting, network evolution, revenue impact, enforcement success, and platform risk assessment. Enables autonomous actions when confidence thresholds are met using prediction and risk assessment tools.
Adaptive Learner Agent
Piracy tactics evolve continuously, and static detection systems degrade in effectiveness without incorporating new patterns and human feedback into their models.
Core Logic
GPT-4o agent with self-improving pattern recognition and strategy optimization. Processes human feedback from HITL decisions, learns new evasion patterns, adapts enforcement strategies based on success rates. RAG-enabled for knowledge accumulation using pattern learning and strategy adaptation tools.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization