Cinder's AI agents enforce your policies at the prompt layer, red-team your models before launch, and keep guardrails calibrated as your product grows. Safety stops being the blocker. It becomes the infrastructure.
Probe your models against real-world abuse patterns before they ship. Our team tests jailbreaks, prompt injection, and policy edge cases at the cadence of modern AI releases, not a once-a-year audit.
Protect your hiring pipeline from synthetic identities, fake credentials, and applicant fraud. Integrated directly into your ATS so vetting happens before access is granted.
Benchmark your models and human reviewers against the same labeled data. Catch policy drift, surface retraining needs, and keep accuracy honest as your product evolves.
Build agents around the specific risks your AI product faces. Trained on your policies, your data, and your team's validated decisions — not someone else's taxonomy.
“Cinder provided rigorous adversarial testing that matched our release velocity. Their team found important edge cases and helped us address them before launch.”
Ben Brooks, Head of Public PolicyBlack Forest Labs
