Problems We Address
Agent risk emerges from the authority assembled around a model: identities, tools, memory, retrieved context, system prompts, integrations, and the ability to act. Teams need to know what an agent can see, what it can change, and how quickly unsafe behavior can be detected and contained.
Orbyntis evaluates those runtime conditions as a connected system. The assessment considers permission scope, data boundaries, credential handling, tool selection, context integrity, approval paths, logging, failure modes, and ownership during an incident.
Engagement Approach
We inventory components and data flows, map trust boundaries, and model misuse and failure paths. Existing safeguards are evaluated against the impact of the actions the agent can perform. Findings are then organized into immediate risk reduction, engineering remediation, and longer-term operating controls.
The work can be performed before a production decision, during architecture refinement, or after a material change to models, tools, integrations, or autonomy.
Enterprise Scenarios
- Reviewing an agent that uses enterprise APIs or privileged service identities
- Assessing memory and retrieved context for sensitive-data or integrity risks
- Designing containment and escalation for unexpected autonomous behavior
- Establishing evidence requirements for security or governance approval
Deliverables are designed to help both technical owners and risk stakeholders make a clear decision about whether and how the workflow should operate.