Unique agent identity
Authenticate each runtime as a distinct workload tied to an owner, team, environment, and deployment.
USE CASE / AUTONOMOUS AGENTS
Give agents capability without giving away authority.
Separate agent identity, action policy, and protected credentials so autonomous systems can complete approved work without inheriting broad human access.
RISK SIGNAL / 01
Agents often receive long-lived credentials with permissions far broader than the specific task they need to perform.
CONTROL GAP DETECTED
CONTROL OUTCOMES
Move from fragmented access to enforceable policy.
Least-privilege actions
Authorize explicit systems, resources, operations, and conditions instead of handing agents unrestricted credentials.
Secretless agent context
Inject credentials only inside the controlled execution path and return the operation result, not the secret.
Complete accountability
Record who delegated authority, which policy allowed it, what the agent attempted, and the final outcome.
REFERENCE ARCHITECTURE
Controls execute in the request path.
Verify identity
Validate a signed workload identity and resolve its enterprise ownership and deployment context.
Parse intent
Normalize the requested tool, operation, resource, parameters, and data boundary.
Authorize execution
Evaluate action policy and inject the minimum protected credential only when allowed.
Return and audit
Return the result without secret material and preserve the complete decision chain.
CONTROL TELEMETRY
ILLUSTRATIVE REFERENCE VIEWTIMEIDENTITYCONTROLRESOURCEDECISION
14:32:08agent.finance-07action_policycrm.accounts.readALLOW
14:31:55app.customer-aimodel_budgetgpt-reasoningROUTE
14:31:41agent.research-12data_boundarydrive.exportBLOCK
TRUST ARCHITECTURE
Built for security review, not security theater.
Map identity, policy, credential use, and audit evidence to the controls your enterprise already operates.
SOC 2 control alignment
Architecture supports evidence collection for access, change, and monitoring controls.
ISO 27001 readiness
Map credential, identity, policy, and audit practices to ISMS control objectives.
NIST AI RMF mapping
Operational visibility across governed model access and autonomous action paths.
Control-alignment statements describe product architecture and are not claims of EnvisionAI certification.
WORKS WITHAWSMicrosoft AzureOpenAIAnthropicGoogle CloudOllama
TECHNICAL EVALUATION
Review the control path with your security and platform teams.
Map the architecture to your providers, identity stack, cloud boundaries, and operating requirements.