Position
Verification is how claims
become trustworthy.
Most autonomous-science systems focus on generation — getting an AI to produce a hypothesis or design. Scivity focuses on what comes after.
Every claim that leaves the platform passes through a multi-stage validation pipeline checking code execution, statistical validity, reproducibility, and scientific plausibility before any conclusion is trusted. A finding only ships if it survives every layer.
What this prevents
The failures that matter most.
- Statistical artifacts that look like discoveries
- Results that don't reproduce on re-run
- Hypotheses that survived selection bias rather than evidence
- Conclusions reviewers couldn't reconstruct from the data
What we share
Outcomes are public.
Methodology is partner-only.
- Industry analysis
Through the AI for Science Landscape — a free, source-backed data hub published under CC BY 4.0.
- Outcome summaries
Validated research output, with reproducibility traces, where the underlying domain is sharable.
- Full methodology
Shared only with research partners under NDA. The platform is proprietary, and the verification approach is part of the moat.
Validation is the gate, not the gloss. If you are building or evaluating autonomous research systems, talk to us.