What evidence do you have that this works?

The platform is grounded in real biological validation, not just retrospective modeling. Predictions are tested in clinically relevant systems, generating prospective evidence that strengthens confidence in decision-making.

In hold-out cross-validation studies, where predictions are compared to unseen experimental data, the predictive layer of the platform, CertisAI™, has been shown to be:

~90%+ accuracy for monotherapy predictions
~80% accuracy for combination therapies

Performance is strongest where training data is rich and more limited in data-sparse areas—which is exactly why the platform is designed to learn. By integrating your data and validating predictions experimentally, the model becomes progressively more accurate for your specific programs over time.