Runtime enforcement for AI agents in production
Enterprises already run agents against real systems. The challenge is no longer model capability, but controlling execution. Norven is a runtime enforcement layer that verifies agent identity, evaluates policy, and records execution context before actions reach production infrastructure.
The execution gap in enterprise agent systems
- •Agent frameworks focus on planning and orchestration
- •Enterprises require identity, authorization, failure control, and auditability at execution time
- •Most teams rebuild this enforcement inconsistently and internally
Norven standardizes this execution boundary without replacing existing frameworks or infrastructure.
Agent reasoning remains probabilistic. Execution is deterministic, enforced, and attributable.
Execution guarantees
Workload Identity
Every agent action is bound to a verifiable workload identity.
Runtime Policy
Actions are evaluated against active policy at execution time.
Durable Execution
Failures are handled deterministically with retry and rollback support.
Execution Provenance
Each decision produces a tamper-evident execution record.
Agent execution lifecycle
Action request
Agent submits a signed request with intent and context.
Policy evaluation
Request is evaluated against the active policy set.
Enforcement
Action is authorized or halted deterministically.
Provenance
An immutable execution record is written.
package main
import "github.com/norven-ai/sdk"
// Bind agent identity
n := sdk.New(sdk.Config{
ID: "agent-3xf",
Key: os.Getenv("KEY"),
})
// Enforce before execution
result, err := n.Enforce(ctx,
sdk.Req{
Action: "customer.read",
Resource: "customer:12345",
},
func() (interface{}, error) {
return db.Find("12345")
})Drop-in enforcement for existing agent systems
- •TypeScript, Python, and Go SDKs
- •REST and gRPC APIs
- •Works with planner-based and workflow-based agents
- •Deployable as shared infrastructure
Designed for internal platform teams
Infrastructure that platform, security, and application teams can rely on for agent deployments
Platform Engineering
Standardize agent identity and execution guarantees across all internal agent deployments
Security Architecture
Enforce execution boundaries and provide audit-grade records for compliance review
Application Teams
Ship agent features without owning infrastructure concerns. Enforcement handled upstream.
Built for enterprises running agents in production
Norven applies the guarantees enterprises already expect from internal infrastructure to AI agent execution. Identity, enforcement, recovery, and provenance are required once agents act on real systems.