Camp Network Solves AI Data Scarcity with Autonomous IP Layer
Camp Network addresses AI data scarcity through its Proof of Provenance protocol, enabling fair compensation for creators and sustainable AI development.
Report by Tiger Research
The AI Data Crisis
AI development faces a critical bottleneck: high-quality training data is expected to be exhausted by 2026. Major models like GPT have already consumed most accessible internet content, leading to:
- Unauthorized data scraping (e.g., Reddit's lawsuit against Anthropic)
- Ethical concerns over uncompensated data usage
- Stalled AI advancement without new data sources
Camp Network's Solution
Camp Network introduces an Autonomous IP Layer with three core components:
-
BaseCAMP & SideCAMP: Blockchain infrastructure optimized for IP transactions
- Global state management with gas-free transactions
- Dedicated execution spaces for AI applications
-
Origin Framework: On-chain IP management system
- ERC-721 NFTs represent IP assets
- Graph-structured royalty distribution
- Dispute resolution via Camp DAO
- mAItrix SDK: AI development toolkit
- Training using only permitted data
- Simplified agent deployment
- Automatic royalty payments
Key Differentiators
- Proof of Provenance Protocol: Verifiable data origins and automated compensation
- 300,000+ registered IPs with 4 million wallets
- $30M Series A funding led by 1kx and Blockchain Capital
Industry Impact
Camp Network creates a new paradigm where:
- Creators maintain data sovereignty
- AI developers access licensed training data
- All participants share in generated value
Future Outlook
As AI agents become ubiquitous, Camp's infrastructure is positioned to:
- Handle real-time IP transactions
- Manage complex derivative content networks
- Become the standard for AI-era data ecosystems
Related Reports:
Related News
Lenovo Wins Frost Sullivan 2025 Asia-Pacific AI Services Leadership Award
Lenovo earns Frost Sullivan's 2025 Asia-Pacific AI Services Customer Value Leadership Recognition for its value-driven innovation and real-world AI impact.
Baidu Wenku GenFlow 2.0 Revolutionizes AI Agents with Multi-Agent Architecture
Baidu Wenku's GenFlow 2.0 introduces a multi-agent system for parallel task processing, integrating with Cangzhou OS to enhance efficiency and redefine AI workflows.
About the Author

Dr. Emily Wang
AI Product Strategy Expert
Former Google AI Product Manager with 10 years of experience in AI product development and strategy formulation. Led multiple successful AI products from 0 to 1 development process, now provides product strategy consulting for AI startups while writing AI product analysis articles for various tech media outlets.