Runtime Assurance for Enterprise, Autonomous and Edge AI.
Secure AI systems end-to-end with visibility and protection across development, runtime, and post-incident response.
Detect & Respond to Unsafe AI Behavior
Most AI risk doesn’t emerge in development—it appears at runtime. Without continuous visibility into AI decisions and actions in production, hidden failures can quickly turn into safety incidents, downtime, and regulatory exposure across edge and autonomous systems.
- AI failures emerge at runtime, not in design reviews.
- Lack of visibility into AI decisions hides unsafe or unstable behavior.
- At the edge, small AI errors can quickly become real-world incidents.
Validated, optimized, and trusted AI.
Securing AI Models & Agents.
Ensure AI models and agents are safe, aligned, and fit for real-world operation before they reach production.
- Validate models and agents against real-world data, environments, and hardware constraints
- Identify unsafe, misaligned, or high-risk behaviors early
- Assess the security impact of model, prompt, agent, or environment changes
- Establish behavioral baselines to define what “safe” operation looks like
Outcome: Only trusted, fit-for-purpose AI systems are deployed.
Continuously observe how AI systems behave once deployed, where most security risk actually emerges.
- Monitor AI-driven decisions and actions in production and at the edge
- Detect anomalous, unsafe, or out-of-policy behavior in real time
- Track decision-to-action chains to understand how AI outputs affect systems and operations
- Identify behavioral drift caused by data shifts, environment changes, or updates
Outcome: Security and safety issues are detected before they escalate into incidents.
Act quickly when risk appears and ensure incidents lead to stronger AI security over time.
- Enforce automated guardrails to prevent unsafe AI-driven actions
- Support rapid incident investigation with decision-level forensics
- Maintain runtime evidence and audit trails for security, compliance, and accountability
- Feed lessons learned back into validation to prevent repeat failures
Outcome: Faster response, reduced impact, and continuously improving AI security.
Starseer offers visibility and controls across your AI models and agents.
Many solutions focus on isolated checkpoints, policy, testing, or pre-deployment controls, but fail to provide continuous visibility into decision-to-action behavior once AI systems are deployed and operating in real-world, edge, and autonomous environments.
Support to secure and remediate your AI models & agents.
