Luel

Luel is a multi-modal data lab powering the foundations of machine perception, built upon a proprietary continuous data engine that trains AI systems to seamlessly listen, reason, and act. The company provides curated, rights-cleared training data from verified contributors for AI applications, connecting enterprises with contributors to create high-quality datasets through a marketplace model. Luel offers custom sourcing, verified quality, and fast delivery of training data, with the platform facilitating earning opportunities for contributors through content creation. The company's approach addresses the critical bottleneck in AI development: the acquisition of high-quality, legally cleared training data that enables enterprises to build and refine AI models without intellectual property risk. By maintaining a network of verified contributors and a continuous data engine, Luel enables organizations to source domain-specific, multimodal training data that meets their exact specifications, whether for computer vision, natural language processing, audio processing, or multi-modal AI systems. The marketplace model creates a two-sided ecosystem where contributors are compensated for creating and contributing data, while enterprises gain access to diverse, high-quality datasets that would be difficult or expensive to produce internally. Founded in 2026 and headquartered in San Francisco, California, Luel has raised $31.7M in seed funding from investors including Y Combinator, General Catalyst, Lightspeed Venture Partners, Orange Collective, and Human Capital. The team comprises 99 employees.

AI Infrastructure > Marketplaces > AI Models Marketplace

College Wise > University of California (Berkeley)