Regular Testing for AI Teams
Integrate robustness testing into your development cycle
Your models evolve. Does your security testing?
Every model update, fine-tuning run, or dataset change can introduce new vulnerabilities. Serious AI teams test adversarial robustness at every iteration — not just before the initial deployment.
Typical use cases
Post-fine-tuning testing
Validate that fine-tuning on business data hasn't degraded the adversarial robustness of the base model.
Model comparison
Objectively compare the robustness of multiple architectures or versions before choosing which to deploy.
Deployment gate
Integrate a minimum robustness score as a mandatory gate criterion before production deployment.
Client documentation
Provide clients with independent technical reports at every model delivery.
Longitudinal tracking
Track how your model's robustness evolves over time with timestamped, verifiable reports.
EU AI Act preparation
Build your technical file now for Article 15 obligations (high-risk systems).
Integration into your workflow
Submit model
Local CLI — no weights transmitted
Automated tests
Full suite per your AI domain
PDF report
Score, metrics, recommendations
Repeat
At every iteration or delivery
Volume, subscription or custom
For teams that test regularly, we offer adapted plans: token packs, monthly subscriptions, or enterprise contracts with SLA and dedicated support.
See pricingLet's discuss your needs
Every team has different constraints. Contact us for a plan adapted to your volume and workflow.