Human Native AI
Ethical data marketplace for licensing AI model training.
| Date | Investors | Amount | Round |
|---|---|---|---|
| investor investor | €0.0 | round | |
N/A | Convertible | ||
| Total Funding | 000k | ||
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Human Native AI is a London-based company founded in 2024 by James Smith and Jack Galilee to create a fair and ethical data ecosystem for artificial intelligence. The company operates a data marketplace that connects data rights holders with AI developers, ensuring creators are compensated for the use of their work in training AI models. This platform addresses the legal and ethical concerns surrounding the use of copyrighted content to train large language models (LLMs) by providing a catalog of fully licensed, rights-cleared data.
The founders' backgrounds informed the company's mission. James Smith's experience at Google, particularly in shipping a DeepMind model on Android, highlighted the critical challenge of sourcing high-quality, safe, and reliable data for AI development. This experience, coupled with the observation that rights holders were largely uncompensated for their data's use in the burgeoning generative AI field, served as the catalyst for the company's creation.
Human Native AI's business model revolves around its marketplace, which facilitates various licensing agreements, including subscriptions, revenue-sharing, and per-use payments for retrieval-augmented generation. For AI developers, the platform streamlines the data acquisition process, providing ready-to-use, benchmarked datasets that mitigate legal risks and reduce data preparation time. For rights holders, such as publishers and creative professionals, the company offers tools to index, evaluate, and monetize their content, providing control over how their intellectual property is used. The firm has already attracted clients like Mumsnet and Reach, the publisher of The Daily Mirror. In June 2024, Human Native AI secured £2.8M ($3.57M) in a seed funding round led by LocalGlobe and Mercuri to expand its team and product development.
Keywords: AI data marketplace, data licensing, ethical AI, copyright, large language models, training data, intellectual property rights, data monetization, responsible AI, data rights holders, generative AI, machine learning data, AI compliance, content licensing, data-sets, AI ethics, data brokerage, AI law, rights clearance, digital content licensing