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Open weight model safety

Deploy open-weight models with frontier safety built in

Cinder helps teams launching or fine-tuning open-weight models move fast without treating safety as a one-time report: red-team the model, operationalize the findings, and keep safeguards improving through release.

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Launch readiness

Safeguards for every stage of an open-weight release.

The work starts with adversarial testing, then turns findings into the operating loop your team needs after launch.

Pre-release red teaming

Find policy failures, jailbreak paths, and multimodal safety gaps before weights reach users or downstream builders.

Safety eval operations

Turn adversarial findings into repeatable evals, QA sets, thresholds, and launch-readiness evidence.

Guardrail improvement loops

Use red-team findings to improve safeguards, policies, evals, and review workflows before and after release.

Release governance

Keep model, policy, product, and safety owners aligned on what is resolved, what is accepted, and what still needs review.

Perspectives

Read the latest thinking behind the push.

  1. 01The Real AI Safety Problem Is Already HereGlen Wise on why open-weight adoption is forcing a new conversation about data retention, privacy, and safety infrastructure.
  2. 02AI Safety Is the Goal. Safeguards Are the Work.A perspective on moving from AI safety as an objective to safeguards that teams can deploy, test, monitor, and enforce.

Approach

Red-team the model. Improve the guardrails. Govern the release.

  • Synthetic red teaming to expose abuse paths and safeguard gaps.
  • Structured findings that feed evals, policy updates, and guardrail training.
  • Launch-readiness workflows for unresolved risks, owners, and signoff.

Open-weight releases compress the timeline between model availability and real-world misuse. Safety teams need evidence quickly, but they also need a system for acting on what the evidence shows.

Cinder pairs adversarial testing with the operational layer around it: policy-aligned evals, review workflows, launch decisions, QA, and feedback loops that help teams keep pace as weights, fine-tunes, and downstream use cases change.

“What Synthesia needs now is infrastructure that can keep pace with how quickly the product and the threat landscape are moving, which is why Synthesia is combining its know-how with Cinder's technological capabilities.”

Synthesia

>90%

Reduction in CSAM and NCII vulnerability

10X

Safer than benchmark industry models at launch

Read case study

Talk with Cinder about a focused red-team and launch-readiness push for your next open-weight model release.

Get a demoRead the BFL case study