Agentic Guardrails: context for AI agent decisions
Avistar Raio gives AI guardrails the facts they need: who the agent runs as, what it can do, and whether the action meets your controls.
Guardrails that live inside the model can be talked out of it
AI agents often run on credentials nobody scoped, rotated, or monitored.
Guardrails live inside the model
Prompt instructions, judges, and reasoning chains can be renegotiated by the same agent they are meant to control.
Identity is broader than the task
Agents often inherit identities with far more reach than the job requires, and the gap is rarely visible.
Evidence, not transcripts
Auditors need control coverage, not a log of what the model said it checked.
Two layers, cleanly separated
Raio supplies context. Your enforcement layer decides. The separation makes each decision verifiable.
Avistar Raio: context
Knows the identities, effective permissions, scopes, blast radius, and control bindings of your cloud tenant.
Enforcement layer: decision + proof
Consumes the facts, applies policy, and emits a verifiable record of the decision without living inside the model.
Raio does not sit in the request path and does not make the allow or deny call. It is the source of truth the decision is made against.
Discovery and decision are decoupled
Raio builds identity context ahead of time and serves only the facts needed for each decision.
Cadenced scanning
Raio scans on a schedule to capture identities, effective permissions, reachability, and posture drift.
Context library
Results are normalized into a typed identity graph, stored for low latency retrieval at decision time.
Retrieval at decision time
When an agent proposes an action, the enforcement layer queries only the facts that action implicates.
Verifiable enforcement
Every decision is paired with a record of the context it was evaluated against, so allows and blocks are both auditable.
Freshness is explicit, not implied.
Every fact carries a scan timestamp, so a decision can require context newer than a stated age and fail closed otherwise.
Facts that turn guardrails into evidence
- Effective permissions, not declared ones
- Blast radius of each identity
- Least privilege delta
- Control bindings to common frameworks
- Prompt and injection screening
- Drift detection between scans
Control coverage, not just transcripts
Context is expressed against the frameworks customers already report on, so a decision produces control evidence rather than a log line.
A preflight check before an agent takes off
Denied actions are as valuable as approved ones. Each produces a precise statement of what was missing and which control it would have violated.
Prompt or agent action arrives
Raio is queried for identity context
Required controls for this action are resolved
Enforcement layer decides: satisfiable or not
Proof and coverage record are emitted
Three ways to integrate
All three keep the same boundary: Raio supplies context, the enforcement layer enforces.
Library
Raio embedded as a context client inside your enforcement layer.
Sidecar collector
Raio runs alongside, publishing context to the store the enforcement layer reads.
API
Raio exposed as a hosted context API for the enforcement layer to query.
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