Category Definition
Gantral defines a new category:
AI Execution Control Plane
This category is distinct from existing AI tooling markets.
What Exists Today
Most AI platforms are agent-centric:
- Agent builders focus on creating intelligent behavior
- Observability tools focus on monitoring outputs
- Governance registries focus on cataloging agents
Enterprises, however, operate in a process- and accountability-centric model.
This mismatch creates execution chaos at scale.
The Missing Layer
What is missing is a shared, infrastructure-level control layer that:
- Enforces who can decide
- Records what was decided
- Governs how AI participates in processes
- Decouples policy from agent code
This is the AI Execution Control Plane.
How Gantral Differs
| Dimension | Agent Builders | Governance Tools | Gantral |
|---|---|---|---|
| Focus | Intelligence | Inventory & policy | Execution & authority |
| Unit of Control | Agent | Agent | Instance |
| HITL | Optional / ad-hoc | Reported | Enforced via execution-state transitions |
| Audit | Logs & traces | Metadata | Deterministic replay |
| Scope | Single workflow | Registry-level | Cross-process |
Gantral does not compete on intelligence.
It competes on control.
Why This Category Matters Now
This category is emerging in response to observable enterprise adoption patterns.
- AI adoption across material workflows
- Regulatory pressure on AI decisions
- Cost, accountability, and audit requirements at scale
As with containers, infrastructure-level control emerges only after chaos becomes visible.
Gantral exists because that point has been reached.