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DataNexx

Evaluation & benchmarking

Evaluation sets with ground truth you did not generate yourself.

Benchmarks built from public data leak into training sets. Held-out proprietary records with verified outcomes give you evaluation signal that has never been on the internet.

  1. 01 →The physical worldSamples, materials, machines, batches
  2. 02 →MeasurementsInstruments, sensors, test rigs
  3. 03 →Expert decisionsTechnicians, engineers, operators
  4. 04 →Verified outcomesPass / fail, failure mode, result
  5. 05 →Structured dataDocumented, de-identified, licensed
  6. 06 AITraining, evaluation, RL, agents

What matters

What this data needs to have.

  • 01

    Verified answers

    Each record carries an outcome determined by a qualified person or a physical test.

  • 02

    Contamination resistance

    Data that has never been published is far less likely to appear in pre-training corpora.

  • 03

    Hard cases

    Long histories surface rare failures and edge cases that synthetic suites miss.

Typical data shapes

  • Pass / fail determinations
  • Failure-mode classifications
  • Expert interpretations
  • Root-cause analyses

Relevant categories

How sourcing works

You tell us what your model needs.

We find organizations that produce it and help them prepare it responsibly.

Dataset specificationExample
Industry
Materials testing
Desired records
100,000+ laboratory tests
Desired structure
Inputs + measurements + verified outcomes
Modalities
Structured data, images, documents, signals, video, audio
Geography
Any, or specific regions
Time period
2015 – present
Exclusivity
Non-exclusive acceptable
Rights requirements
Commercial training rights, documented provenance
Intended use
Training, evaluation, RL, benchmarking, research
  1. 01

    Specify

    Tell us what your model needs: domain, structure, modalities, scale, time period, rights and intended use.

  2. 02

    Source

    We identify and approach organizations that naturally generate matching data — including data that does not yet exist as a packaged product.

  3. 03

    Qualify

    We evaluate whether candidate data can be licensed and whether it meets your structure and quality bar. You review anonymized descriptions and documentation before anything moves.

  4. 04

    Prepare

    We work with the data owner to de-identify, structure and document the data to your specification.

  5. 05

    License

    Terms, scope and permitted uses are set out contractually. Delivery follows only with the data owner's authorization.

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.