AI gets better when it understands the human in front of it.
We build the infrastructure that makes that possible.
Open Data Labs is an applied research institute. We develop technology that helps AI understand the humans using it.
ODL is focused on one question: where does AI get the context it needs? Not from bigger models. Not from synthetic data. From the user, with consent.
We work with AI teams at every stage. Whether you’re scoping your first pilot or scaling a model in production, your product needs to know who it’s talking to. We make that possible.
Infrastructure for every layer, from training data to runtime context to agentic commerce.
Case studies, research, and press.
Fortune 500 fashion brand builds real-time taste prediction engine.
A Fortune 500 fashion retailer used primary source datasets to infer style preference before a customer had any purchase history.
Open Problems in AI Data Economics
We introduce data economics as a coherent field and define the open problems that haven’t yet been formalised. Most AI economics research focuses on downstream effects. We argue you can’t understand AI’s economic trajectory without studying how data, compute, and labour interact at the production layer.
Thweet creates 1,497 one-of-one guest experiences.
Thweet turned one creative concept into 1,497 personalised experiences during Korea Blockchain Week 2025.
Vana lets users own a piece of the AI models trained on their data
MIT News on the founding story, the Media Lab origins, and the case for user-owned AI.
Frontier AI Lab sources real human conversation data with consent, redaction, and provenance.
A frontier AI lab used Context Gateway to source real human conversational data with documented consent, redaction, and provenance.
Model Influence Functions: Measuring Data Quality
A framework for attributing model outputs to training data contributions. The methodological foundation for pricing and valuing datasets in commercial AI pipelines.