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Omida AI
Safety / Frontier

A framework for increasingly capable systems.

The evaluation and deployment questions we intend to address as our model and agent work develops.

A framework in development

Omida has not released a frontier model or published a frontier-model safety evaluation here. This is an outline of the work that future deployment decisions would need. It is not a claim that these processes have already been implemented or passed.

Evaluate the actual system

Assess a model in the conditions where it will be used, including tools, memory, permissions and the people relying on it. Define the tasks, document the methods and look beyond aggregate scores to recurring and high-consequence failures.

Identify how capability can become risk

Consider misuse, unsafe autonomy, security failures and misleading confidence. Adversarial testing should probe the system’s boundaries rather than only demonstrate a successful workflow.

Set deployment boundaries

Before release, specify permitted actions, the need for human review, access constraints and what would cause a deployment to pause. Uncertainty should be part of that decision, especially where tests do not cover a proposed use.

Monitor and revise

A pre-release evaluation cannot anticipate every real-world condition. Reporting channels, incident analysis and the ability to change or withdraw a capability should accompany deployment.

Publish with context

For future model releases, we intend to make evaluation methods, limitations, safeguards and availability understandable in the model documentation. No numerical risk thresholds or certification claims are being announced on this page.