Prompt evaluation
Assess prompts before execution to identify risky instructions, policy conflicts, and misuse conditions.
Runtime Control Plane
Governance that reaches execution time
Runtime guardrails push governance into the decision path of AI applications so organizations can observe, constrain, and improve behavior where it actually occurs.
Runtime control
Prompt, output, and tool-call guardrails in one control path
Output evaluation
Inspect model outputs for policy violations, unsafe content, leakage patterns, and quality concerns.
Tool-call evaluation
Evaluate tool usage in agentic systems before allowing external actions, data retrieval, or sensitive operations.
Decision telemetry
Capture allow, modify, and block decisions with context for runtime observability and governance evidence.
Platform proof
Observable runtime decisions
Runtime guardrails
Guardrail design and runtime evaluation over prompts, outputs, and tool calls.
Issue detail and evidence
Technical context, governance implications, and next actions in the same incident surface.
Compliance mapping
Framework-aligned governance evidence and control coverage in a real operational view.
Next step
Move governance into runtime
Guardrails matter when they can make decisions in execution time and leave evidence behind.