Make your data work for you.
Explore a new revenue stream from the knowledge, workflows, and records your business already creates. Start with the data you can authorize for licensing.
Explore selling your data ↗From robotics demonstrations and audio conversations to code and business workflows, your company’s data holds extraordinary value. We buy and license it, then prepare it for the AI labs building what comes next.
Companies create the experience.
Labs turn it into intelligence. We connect the two.
Explore a new revenue stream from the knowledge, workflows, and records your business already creates. Start with the data you can authorize for licensing.
Explore selling your data ↗Source hard-to-find company data grounded in real work. Define the domains, formats, and capabilities you need for training and evaluation.
Discuss your data needs ↗Explore examples of data we can seek through company partnerships. These are sourcing categories, not a live inventory.
Connect implementation decisions to the problems and outcomes behind them.
Explore ↗Learn how people and machines interact with the physical world, from object manipulation to equipment operation.
Explore ↗Build speech and voice capabilities with real-world calls, interviews, and natural conversations across languages.
Explore ↗Learn from multi-step problem solving and customer support outcomes.
Explore ↗Capture how real organizations plan, execute, and handle edge cases.
Explore ↗Bring industry-specific context to training and evaluation datasets.
Explore ↗Every partnership starts with a clear use case, a defined scope, and agreed data rights.
Map a company’s available data to a lab’s research needs. Evaluate relevance, coverage, quality, and permitted uses before a deal.
Define the purchase or license, compensation, permitted recipients, and usage boundaries. Address confidentiality and third-party rights.
Scope filtering, de-identification, formatting, and quality checks for the intended use. Deliver against agreed acceptance criteria.
Useful data captures knowledge or workflows that are difficult to find publicly. Context, consistent structure, clear outcomes, and permission to license can matter more than raw volume.
No. A partnership can be structured as a scoped license or a purchase. Exclusivity, duration, recipients, and permitted training or evaluation uses are negotiated for each agreement.
The data scope and handling requirements are defined before transfer. Depending on the dataset, preparation may require removing personal information, excluding confidential material, or limiting access. Only authorized data belongs in a partnership.
Yes. Start with the model capability or evaluation need, then specify domains, formats, approximate scale, and licensing requirements. A clear sourcing brief makes it easier to assess fit.
Turn valuable data into a valuable partnership.