Gamut Gateway
The control point before AI agents act.
Gamut Gateway evaluates proposed AI actions before execution. It applies policy decisions, approval gates, connector boundaries, model-provider egress control, data rules, logging and evidence capture so agentic workflows become visible, bounded and reviewable.
Book a callWhy Gateway exists
Agentic AI changes the risk equation. A traditional AI system may generate an answer. An agent can call a tool, retrieve data, update a system, send a message, create a ticket, invoke a model or trigger a workflow. Gateway is designed to create a decision point between AI intent and business action.
Do not trust action by default
An agent should not act simply because it can. Actions need policy checks, boundaries and approvals before execution.
Separate decision from execution
Gateway decides whether an action is allowed, blocked, logged or escalated before Claw or a workflow proceeds.
Make control evidence visible
Every important decision can become assurance evidence for security, audit, leadership and incident review.
What Gateway controls
Policy decisions
Evaluate proposed action against autonomy level, owner, risk state, target system, data class and approval requirement.
Tool and connector access
Route approved calls through configured connectors with endpoint validation, path allowlists, bounded payloads and response controls.
Model-provider egress
Control model invocation through a governed egress path rather than allowing execution workers to call providers directly.
Approval gates
Require human approval before high-impact actions, sensitive data access, external communications or operational changes.
Data boundaries
Apply data classification, redaction, payload limits and response controls before information moves through AI workflows.
Runtime evidence
Record decisions, allowed actions, blocks, escalations, connector use, findings and enforcement outcomes.
Gateway-mediated action patterns
- Model invocation after Gateway policy approval
- RAG search and retrieval with bounded, cited and redacted output
- MCP tool calls through approved server boundaries
- SIEM and SOAR security actions through approved connectors
- Read-only database queries under strict query policy
- Configurable HTTP API requests
- Webhook sends to approved destinations
- Code repository actions under scoped repository permissions
- Gamut writeback for approved findings and evidence requests
- Escalation when policy, data class or risk state requires review
Security controls buyers can understand
| Control | Why it matters |
|---|---|
| Environment-backed credential references | Raw customer secrets are not stored in Gamut tables and are not handed directly to Claw. |
| Endpoint and origin validation | Connector calls are restricted to approved endpoints and cannot escape to another origin. |
| Path allowlists | HTTP, webhook and repository connectors can be limited to approved route patterns. |
| Bounded request and response sizes | Payloads and responses are size-limited to reduce abuse, data leakage and uncontrolled execution. |
| Response redaction | Connector output can be redacted before storage, workflow use or display. |
| Audit evidence | Gateway decisions, connector use and enforcement outcomes become evidence for assurance and incident review. |
What Gateway helps you prove
- Which agents attempted which actions
- Which actions were allowed, blocked or escalated
- Which policies and approvals applied
- Which tools, systems and connectors were involved
- Which data boundaries were enforced
- What runtime evidence was captured
- What incidents or exceptions require review
- What control improvements are needed next
How Gateway fits into the Gamut operating stack
Gamut AI is the system of record. Agentic CISO records agent risk and assurance context. Gateway is the enforcement layer. Claw is the bounded execution worker. Together, they give teams a defensible way to govern AI-enabled action rather than simply documenting agents after the fact.
Explore agentic AI governance · See Claw · View the 30-day sprint
Control before execution
Put policy, approval and evidence between AI intent and business action.
Use Gamut Gateway to make agent actions visible, bounded, approved and reviewable before they affect data, systems, customers or operations.
Book a call