Models published with their limits.
Weights are one output of a lab. We put the same care into the datasets, baselines, limits and failure cases around them.
Open model research
Each of these has a public model card or source. Usage conditions and limitations are on each project page.
How we evaluate
Different fields have different failure costs. A wrong answer in a shopping recommendation is an annoyance. In a safety observation it is not.
Start with a baseline
Compare against a simple, credible alternative before investing in a model-heavy approach.
Measure outside the demo
Check edge cases, language coverage, latency, reliability and the failure modes specific to the task.
Write down the limits
Record data provenance, evaluation design, intended use and restrictions next to the results.
Design the handoff
Decide what people review, how outputs are logged and how the system is revised after deployment.
Across software and physical systems
Our founder, Emmanuel Ashinze, has a research background spanning industrial computer vision, petroleum engineering, energy systems, flow assurance and domain language models.
Have a research question?
Feasibility studies, evaluation design and model work are all good places to start.
Start a project