Real-world signals for scientific AI
We work with labs and field teams to capture scientific observations as they happen, then curate them into provenance-rich training and evaluation data for science models.
Partner with usCaptured where the work happens
Science operators record observations in the field and at the bench with lightweight capture — the conditions, deviations and outcomes that never reach a paper.
Field capture
Provenance on every record
Source, method, instrument, permissions and consent are normalized into one schema, so any observation can be traced back to where it came from.
Traceable by design
Delivered model-ready
Human validation and structured quality checks turn raw observations into training and evaluation sets your team can load straight into a run.
Training and eval sets
Data that published corpora cannot reproduce
Most of the context behind a result never makes it into the literature, and sharing what does exist across institutions is still slow work. We build the missing layer instead: new observations, captured with permission and kept traceable from the bench to the batch you train on.
- Normalized metadata, provenance and permissions
- Human validation at the point of capture
- Evaluation sets built from observations no corpus has seen
Building a science model? Let us capture what your corpus never saw.
Tell us which observations your work depends on, and we will scope a capture programme around them.
Partner with us