Compare · Guardrails
Skipr and AI guardrails
Guardrails are content controls: filters, refusals, prompt defences, output validation. They make model behaviour safer. They do not determine whether the tool call the model triggers is permitted to run against a production system.
What AI guardrails does well
- Filtering harmful, sensitive or off-policy content
- Reducing prompt injection and jailbreak success rates
- Validating output structure before downstream consumption
- Applying per-application safety policy close to the model
Where it stops
- They operate on text, not on the action the text triggers
- They are configured per application, so coverage is uneven across the estate
- They cannot verify the principal or apply jurisdictional policy
- A compliant response can still precede an unauthorized tool invocation
What changes with autonomous execution
- Agents convert output into execution against real systems and data
- The consequential decision has moved from what is said to what is done
- Evidence must cover the action, not the completion
How Skipr complements it
- Guardrails stay where they are, at the model boundary
- AgentConnect governs the tool call, the data access and the agent-to-agent hop
- Policy and residency are applied per action, independent of which model produced the request
Side by side
| Dimension | AI guardrails | Skipr |
|---|---|---|
| Object of control | Model output | System action |
| Scope | Per application or model | Across the estate, any vendor |
| Identity awareness | Limited | Verified principal per action |
| Evidence | Filter events | Signed decision and executed action |
Questions
- Should I remove my guardrails?
- No. They address a real class of risk at the model boundary. They are not an execution control.
- Does Skipr inspect prompts?
- Skipr governs the actions a system attempts. Content safety at the model boundary remains the guardrail's job.
- What if the model is jailbroken?
- The attempted action still has to pass identity, context and policy at runtime before it can execute.
Continue
Other comparisons
- AI governance and runtime governanceAI governance decides and documents what should be allowed. Runtime governance enforces it in the path of the action and proves the outcome. Both are needed.
- Skipr and identity and access managementIAM establishes who a principal is and what they may reach. Skipr decides whether a specific action may execute right now, and proves it.
- Skipr and privileged access managementPAM controls privileged sessions and credentials for administrators. Skipr governs every action — human, agent, application or machine — at runtime.