The governance layer for AI agents
Clasper is a governance-first control plane for AI agents. Deploy it as governance-only, or add the optional stateless runtime for execution. OS/browser actions always stay in your backend.
Trusted for production workloads
The Problem
AI agents do not fail gracefully in production. Most agent frameworks optimize for capability. Very few optimize for operability. That gap is where production incidents happen.
Unapproved Actions
Agents executing high-stakes actions without explicit approval, bypassing human oversight entirely.
Unpredictable Behavior
Stochastic models changing behavior without explanation, making debugging and reproduction impossible.
Silent Costs
Runaway token usage and API calls racking up bills silently in the background with no budget enforcement.
No Audit Trail
Black-box execution leaves no usable logs for compliance, security reviews, or incident post-mortems.
No Rollback
Once an agent acts, it's done. No state management to revert changes or compensate for failed steps.
Tenant Leakage
Cross-tenant data exposure when agents access resources without proper isolation boundaries.
What Clasper Is
Clasper is a governance-first control plane for AI agents. It can run in governance-only mode or with the optional stateless runtime for execution. It never executes OS or browser actions directly.
"Governance, audit logs, and cost visibility for agent execution."
> risk_score: available
> cost_tracking: enabled
> trace_view: ready
Two Ways to Deploy
Start governance-first, then choose whether Clasper also runs the stateless runtime.
Governance-Only
Use the Ops Console and governance APIs to audit, review, and control agent behavior while execution remains in your existing runtime or backend systems.
Governance + Execution
Add the stateless Clasper runtime to handle LLM execution via API while keeping all OS, browser, and data actions in your backend.
How It Works
Agents submit requests. Clasper records context, evaluates governance signals, and makes every execution traceable in Ops.
Agent Runtime
POST /api/agents/send (runtime mode)
Clasper
- Policy Context
- Risk + Cost Signals
- Audit Log
Execution
Backend APIs / OpenClaw
Core Capabilities
Governance and Safety
Ops Console RBAC, tenant isolation, immutable audit logs, redaction, and break-glass overrides for ops actions.
Observability and Explainability
Trace views, replay, diff, and labels for recorded executions, plus audit trails for ops changes.
Change Control
Workspace versioning, environment pins, promotions, and rollback workflows with audit trail.
Cost and Risk Intelligence
Cost tracking, usage dashboards, and risk scoring available via Ops APIs.
Designed for Real Systems
Built for multi-tenant SaaS platforms, regulated environments, and platform teams shipping agent capabilities internally.
Clasper is NOT
- A personal AI assistant or OS-level automation runtime
- A chatbot framework
- A source of truth for your data
- Autonomy-first by default
Clasper NEVER
- Self-initiates actions without a request
- Stores agent memory (stateless)
- Executes OS/browser actions directly
- Schedules autonomous background jobs
Open by Design
Governance infrastructure must be inspectable. Trust beats lock-in. Standards matter more than hype.
Open Source Core Includes
Deployments
Production Principles
Clasper is built on the belief that AI agents are not demos—they are software.
Determinism Over Magic
If an agent cannot be replayed, it cannot be trusted. Every decision must be traceable, inspectable, and reproducible.
Skills Are Software
Prompts are not vibes. Skills are versioned, tested, permissioned, and immutable. If it can't be tested, it doesn't ship.
Safety as Default
No implicit access. No silent escalation. No cross-tenant leakage. The safest path is always the default path.
Why Teams Adopt Clasper
"We can't explain what our agents are doing — and that's unacceptable."
Clasper gives you confidence to ship, proof for auditors, and control when something goes wrong.
Start with trust. Scale with confidence.
Ready to govern your agents?
Read the docs, explore the repos, or talk to us about your execution model.