Perle, an innovative AI training data platform leveraging Web3 technology, has successfully raised a $9 million seed round led by Framework Ventures. This funding, bringing the company’s total to $17.5 million, marks a significant step in Perle’s mission to enhance AI model training through high-quality, human-verified data. The capital will fuel the launch of Perle Labs, a crypto-native ecosystem designed to revolutionize human-AI collaboration.
Perle secures $9M seed round led by Framework Ventures.
Total funding reaches $17.5M for AI data training platform.
Perle Labs uses Web3 for transparent, incentivized data contributions.
Human-in-the-loop annotation outperforms Amazon Rekognition by 70%.
Platform supports multimodal data and reinforcement learning.
Aims to reduce bias and improve AI with diverse, verified datasets.
Perle’s platform integrates blockchain to create a transparent, incentivized system for data annotation and evaluation. Perle Labs enables global contributors to provide high-quality data, with on-chain attribution and verifiable work histories ensuring trust and scalability. This approach addresses the critical need for diverse datasets to train sophisticated AI models, particularly for complex, context-specific scenarios. "As AI models grow more sophisticated, their success hinges on how well they handle the long tail of data inputs—those rare, ambiguous, or context-specific scenarios," said Ahmed Rashad, CEO of Perle. "In our benchmarking, we've seen high-quality human-in-the-loop annotation outperform Amazon Rekognition by over 70%—proving that thoughtful human input is essential to closing critical data gaps."
Perle Labs leverages Web3’s decentralized infrastructure to reward contributors and ensure data integrity. By combining blockchain’s transparency with AI’s need for accurate data, Perle creates a scalable ecosystem that reduces bias and enhances model performance. "We believe the pace of AI progress will be driven more by better data than by simply scaling models," said Vance Spencer, Co-Founder of Framework Ventures. The platform supports the full AI development lifecycle, including multimodal data collection (audio, image, video) and reinforcement learning from human feedback (RLHF), enabling companies to scale complex use cases efficiently.
Founded by AI experts from Scale AI, Meta, MIT, and Berkeley, Perle brings deep technical knowledge to its mission. The company’s self-serve platform streamlines data collection, annotation, and evaluation, delivering faster and more accurate results. With this $9M round, following an $8.5M seed round in October 2024 led by CoinFund, Perle is well-positioned to expand its network and impact. The company’s focus on high-quality human feedback ensures AI progress is not only rapid but also ethical and inclusive.
Perle’s innovative approach positions it as a leader in AI data training, combining Web3 incentives with human expertise to create smarter, safer AI systems. As the company scales Perle Labs, it aims to empower a global community to shape the future of AI with high-quality, verified data.
Perle transforms how AI teams access and use training data by combining human expertise with adaptive workflows. Specializing in data acquisition, expert annotation, and model evaluation, Perle delivers faster, more reliable results tailored for generative AI, LLMs, and RLHF. Our approach ensures data quality and context where it matters most-helping teams build smarter, more trustworthy AI.
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