Perle Secures $9M Seed Round for Web3 AI Data Training Platform Launch
Perle, an innovative AI training data platform, has successfully closed a $9 million seed funding round led by the prominent crypto-native venture firm, Framework Ventures. This significant investment brings Perle’s total funding to $17.5 million across its pre-seed and seed rounds, marking a substantial milestone in the company’s ambitious mission to infuse artificial intelligence models with enriched human wisdom.
The core of Perle’s offering lies in its Web3-powered approach, designed to address a critical challenge facing the rapidly evolving AI landscape: the increasing scarcity and declining quality of human-generated training data. As AI models grow in sophistication, their performance hinges on the quality and diversity of the data they learn from; however, existing systems often struggle with nuanced, ambiguous, or context-specific scenarios. Experts predict a potential shortage of high-quality, natural data for AI training as early as 2026, compelling the industry to seek innovative solutions beyond simply scaling models.
To tackle this, Perle plans to launch “Perle Labs,” a crypto-native ecosystem poised to revolutionize how human input is integrated into AI systems. By leveraging blockchain infrastructure and incentive mechanisms, Perle Labs aims to facilitate transparent compensation, on-chain attribution, and verifiable work histories for contributors. This decentralized approach is designed to unlock global participation, reduce inherent biases, and dramatically improve the overall quality and diversity of training datasets at scale. Perle’s self-service platform supports the entire AI development lifecycle, from collecting multimodal data—including audio, images, and video—to facilitating reinforcement learning from human feedback (RLHF) and fine-tuning assistant models.
Ahmed Rashad, CEO of Perle and a former Scale AI employee, highlighted the impact of this decentralized methodology, stating that it can “unlock global participation, reduce bias, and dramatically improve model performance.” He further noted that Perle’s benchmarking has shown high-quality human-in-the-loop annotation to outperform traditional methods like Amazon Rekognition by over 70%, underscoring the vital role of thoughtful human input in bridging critical data gaps.
Framework Ventures, known for its early investments in key AI, DeFi, and blockchain infrastructure projects, sees a natural synergy in Perle’s vision. Vance Spencer, co-founder of Framework Ventures, emphasized that the pace of AI progress will increasingly be driven by superior data rather than merely by scaling existing models. This investment underscores a growing industry recognition that the future of AI is intrinsically linked to overcoming data limitations through innovative, decentralized mechanisms. The convergence of AI and Web3 is enabling a more distributed, inclusive, and privacy-preserving approach to machine learning, where incentivized participation is key to fostering collaborative AI training environments. As the global AI training dataset market is projected to reach $18.9 billion by 2034, platforms like Perle are positioned to become foundational to next-generation AI development.