AI Control Plane: competitive comparison.
AI control planes provide a centralized layer for governing, controlling and monitoring AI systems in production. Forrester refers to the emerging category as the agentic control plane. This comparison looks at the capabilities enterprises need to operate AI systems safely and reliably at scale, and scores each vendor against its own public documentation.
Within the category the work runs govern, control, observe, assure. Many platforms stop at governance, guardrails and observability. The assurance section is where Brutor continues: it checks, continuously, that each AI system is still operating within its intended behavior, policies and limits.
| Capability✓yes∼partial or claimed–no public claim○not assessed | Brutor | Kong | Prisma AIRS (Portkey) | TrueFoundry | Solo agentgateway | LiteLLM | Gravitee | Netskope | Databricks |
|---|---|---|---|---|---|---|---|---|---|
| AI System Management What runs, who owns it, and what it depends on. | |||||||||
| AI / agent inventory | ✓ | ∼ | ✓ | ∼ | ∼ | ∼ | ∼ | ✓ | ∼ |
| Agent ownership | ✓ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ | ✓ |
| Models, tools and dependencies | ✓ | – | ✓ | ∼ | ∼ | ∼ | ∼ | – | ✓ |
| Governance Policies, identities, guardrails and the frameworks you answer to. | |||||||||
| Policy management | ✓ | ✓ | ∼ | ✓ | ✓ | ∼ | ✓ | ∼ | ∼ |
| Identity and access control | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ∼ | ✓ |
| Guardrails | ✓ | ✓ | ✓ | ✓ | ∼ | ✓ | ∼ | ✓ | ∼ |
| Compliance and risk controls | ✓ | – | ∼ | – | – | – | – | ∼ | – |
| Runtime Control Enforced on every call, not advised after the fact. | |||||||||
| Runtime policy enforcement | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Tool / action control | ✓ | ∼ | ✓ | ✓ | ✓ | ✓ | ∼ | ∼ | ∼ |
| Allow / block actions | ✓ | ✓ | ✓ | ✓ | ∼ | ✓ | ✓ | ✓ | ∼ |
| Usage / budget limits | ✓ | ∼ | ∼ | ∼ | ∼ | ✓ | ∼ | ∼ | ✓ |
| Human intervention | ✓ | – | ∼ | – | ∼ | – | – | – | ∼ |
| Fail-closed / emergency controls | ✓ | ✓ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ |
| Observability and Evidence What happened, what decided it, what it cost, and proof that holds. | |||||||||
| Agent execution visibility | ✓ | ∼ | ✓ | ✓ | ✓ | ✓ | ✓ | – | ✓ |
| Tool / MCP activity | ✓ | ✓ | ✓ | ✓ | ∼ | ✓ | ✓ | ✓ | ✓ |
| Policy decisions | ✓ | ✓ | ✓ | ✓ | ∼ | ✓ | ✓ | ∼ | ∼ |
| Audit trail / provenance | ✓ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ | ∼ |
| Cost / usage monitoring | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ∼ | ∼ | ✓ |
| AI System Assurance Governance, guardrails and observability say what was allowed. Assurance says whether the system is still operating within its intended behavior, policies and limits. | |||||||||
| Define intended behavior / contract | ✓ | – | – | – | – | – | – | – | – |
| Continuous contract adherence | ✓ | – | – | – | – | – | – | – | – |
| Behavioral drift detection | ✓ | – | – | – | – | – | – | – | ∼ |
| Unexpected behavior detection | ✓ | – | ∼ | – | – | – | – | – | ∼ |
| System liveness | ✓ | – | – | – | – | – | ∼ | – | ∼ |
| Assurance status | ✓ | – | – | – | – | – | – | – | – |
| Assurance evidence and reports | ✓ | – | – | – | – | – | – | – | – |
| Cost Control Budgets on the system itself, enforced when it runs. | |||||||||
| Agent / system budgets | ✓ | ∼ | ∼ | – | ∼ | ∼ | ∼ | ∼ | ∼ |
| Cost limits enforced at runtime | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ∼ | ∼ | ✓ |
| Cost anomaly detection | ✓ | – | – | – | – | – | – | – | – |
| Interoperability Any model, cloud, runtime, framework and protocol, without lock-in. | |||||||||
| Multi-model | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Multi-cloud | ∼ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Multi-runtime | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Multi-agent frameworks | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ∼ | ✓ | ✓ |
| MCP | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| A2A | ✓ | ✓ | ∼ | ✓ | ✓ | ✓ | ✓ | – | – |
| Vendor neutral | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ∼ | ∼ |
| Deployment Where it runs. | |||||||||
| Self-hosted | ✓ | ✓ | ∼ | ✓ | ✓ | ✓ | ✓ | ✓ | – |
| Private cloud | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ∼ |
| SaaS | – | ✓ | ✓ | ✓ | – | – | ✓ | ✓ | ✓ |
| Hybrid | – | ✓ | ✓ | ✓ | ∼ | – | ✓ | ✓ | ∼ |
Every cell reflects the vendor's public documentation as of 11 September 2026: a documented, generally available feature is ✓; a beta, a marketing claim without a doc page, or a partial implementation is ∼; nothing found after a real search is –. The Brutor column claims only what docs.brutor.ai documents. Prisma AIRS includes Portkey (acquired by Palo Alto Networks, 29 May 2026). Inline interception of closed apps is a network and browser capability; Brutor brings that AI into the same inventory and ledger through the vendors' own APIs and works alongside your SSE. Field columns are claimed capability, not verified efficacy.
assure, in one sentence
A system can degrade, or die, while every request it makes still returns 200.
That is the failure a request dashboard cannot see, and the reason assurance is a discipline of its own. The white paper sets out the argument, the four guarantees, and what they cost to keep.
