About
Real-world data the internet doesn't have.
DataNexx finds proprietary data AI companies cannot get from the public internet and helps the organizations that created it license it responsibly.
Why we exist
Decades of knowledge, never collected for AI.
Companies around the world have spent decades generating valuable scientific and operational information through tests, measurements, production processes, inspections, experiments, failures and expert decisions.
AI development increasingly depends on high-quality real-world data. Public text is broad but shallow on how real processes behave; synthetic data is only as faithful as the system that generates it.
Meanwhile, laboratories and industrial companies around the world hold decades of measured information that was never collected for AI. It sits in LIMS, MES, historians, QMS archives and file shares — valuable, but dormant.
We exist to bridge that gap responsibly: helping data owners understand what they have, establishing what can be licensed, and connecting qualifying datasets with AI teams that need them. We start with scientific, laboratory and industrial data — where measured, expert-reviewed records are richest — including the process records that show how experts do the work.
Mission
Make real-world scientific and operational knowledge accessible for AI development while protecting the organizations that created it.
- 01 →The physical worldSamples, materials, machines, batches
- 02 →MeasurementsInstruments, sensors, test rigs
- 03 →Expert decisionsTechnicians, engineers, operators
- 04 →Verified outcomesPass / fail, failure mode, result
- 05 →Structured dataDocumented, de-identified, licensed
- 06 AITraining, evaluation, RL, agents
Values
What we hold ourselves to.
- Provenance
- Every dataset should be traceable to how and by whom it was generated.
- Consent
- Data moves only with the authorization of those entitled to give it.
- Transparency
- Buyers and suppliers should understand what is being licensed and on what terms.
- Security
- Sensitive information is handled on a need-to-know basis throughout an engagement.
- Fair compensation
- Organizations that created valuable data should share in the value it creates.
- Scientific integrity
- Data is described as it is — including its limitations.
- Responsible licensing
- We decline data we should not license, even when someone would buy it.
DataNexx does not provide legal advice. Data licensing transactions may require independent legal, privacy, regulatory, or export-control review.
Differentiation
Real-world ground truth, sourced from the people who produced it.
DataNexx finds proprietary data AI companies cannot get from the public internet and helps the organizations that created it license it responsibly.
NOTWeb scraping
Our datasets come from the organizations that generated them, with their authorization.
NOTConsumer data brokerage
We do not trade in personal information about consumers.
NOTSynthetic data generation
We work with measured data. It complements synthetic data rather than replacing it.
NOTA generic dataset marketplace
We source to specification and prepare each dataset with its owner.
NOTAnnotation outsourcing
The expert labels already exist — they were made by the people who did the work.
Own valuable data?
Check your data's licensing potential.
A confidential, no-raw-data assessment of your organization's scientific, industrial or operational records.
Building AI?
You specify it. We source it.
Tell us the proprietary data your model needs — domain, structure, modalities and rights. We approach the organizations that produce it.