Enterprises are not short of AI demos. They are short of a place to run AI responsibly. The Enterprise AI Operating Platform is the control plane that turns scattered model usage into a governed capability — the same way an internal developer platform turned scattered infrastructure into a product.
The control plane
At the centre sits a control plane that mediates every interaction with models: identity, entitlement, routing, cost accounting and audit. Teams do not call providers directly; they call the platform, which makes safety and observability non-optional.
- Model gateway — one governed entry point across providers and self-hosted models.
- Policy & entitlement — who may use which model, on which data, for what.
- Inference plane — autoscaling, caching and routing for cost and latency.
- Agent runtime — sandboxed, observable execution of multi-step workflows.
Teams and workloads
Products, agents, retrieval and evaluation — never a direct call to a provider.
- Product services
- Agentic workflows
- Retrieval
- Evaluation harnesses
AI control plane
One governed entry point across providers and self-hosted models.
- Model gateway
- Policy and entitlement
- Routing
- Cost accounting
- Audit
- Observability
Execution planes
Autoscaled inference and sandboxed, observable agent execution.
- Inference plane
- Caching and batching
- Self-hosted models
- Agent runtime (sandboxed)
- Safe tools
Governed data
Inference moves to the data, not the other way around.
- Governed corpora
- Data stays in jurisdiction
- On-premises and air-gapped topologies
RuleThe governed path is the fast path. If the compliant way to use AI is also the easiest way, shadow AI disappears on its own.
Data gravity and sovereignty
For regulated and sovereign environments, inference moves to the data, not the other way around. The architecture treats air-gapped and on-premises topologies as first-class citizens, not afterthoughts.
Developer experience for AI
The platform exposes golden paths for the things teams actually need: retrieval over governed corpora, evaluation harnesses, and safe agent tools. The goal is the same as ever — reduce cognitive load so teams build products, not plumbing.
Operating model
AI is run as a platform capability with a product owner, SLOs and a cost model. Safety, evaluation and incident response are engineered in, not bolted on after the first regrettable headline.