Mia-Platform vs Hyperscaler Agent Platforms
Strong enforcement inside one cloud. For agentic engineering across clouds, Mia-Platform keeps your AI rules independent of any provider, wherever agents run.
Before you start. A transparent comparison, to help you choose freely. We compare categories, never products.
A note from our leadership
A fast-moving market, and a way to find your bearings.
This comparison is here to help anyone who has to choose in a market that moves fast. It's a transparent comparison, designed to help you understand which category of solutions best fits your needs. We compare categories, never individual products, and we also say where Mia-Platform fits, so you can weigh it with a critical eye.
We share our experience and the public documentation of each category, so that your choice is considered and informed, built on your own use cases.
Francesco Soncini Sessa · CFOFederico Soncini Sessa · COOGiulio Roggero · CTO
Hyperscaler Agent Platforms: three things to take away.
- Where the category shines
A deep, native stack for agents on their cloud.
Runtime, memory, identity, gateway, observability, evaluations and policy from one provider. For agents connected to it, enforcement is strong.
- Where it stops
Your rules end up living in their stack.
Rules are written in one provider's policy model and enforced by its own identity and gateway services. Every extra cloud is another set of services to integrate, coding agents on developer laptops stay outside, and changing provider means rewriting the rules.
Where Mia-Platform fitsYour rules, independent of every vendor.
Agentic engineering spans clouds, laptops and on-prem systems. One rule set covers agents on every cloud and every model, enforced where each agent runs. Mia-Platform can run on top of these runtimes, so you keep them without handing over your governance.
Hyperscaler Agent Platforms, in plain words.
What it is
Hyperscaler agent platforms are the agent platforms of the cloud providers and, in a narrower sense, of model vendors. They provide the runtime, memory, identity, gateway, observability, evaluations and policy engines to build and run agents on their own stack, plus admin controls for their own agents and models.
What it is for
- Building and running agents close to your data and models
- Native identity, access and policy for agents on the platform
- Registries, gateways and audit logs managed by the cloud provider
- Enterprise admin controls for the vendor's own coding agents and models
Why it matters now
Hyperscalers now enforce at the point of action, with registries, identities, gateways and policy engines. So the real question is who owns the rules. On a hyperscaler, governance is assembled from that provider's identity, gateway and policy services: every agent has to be connected to them, every additional cloud brings its own set to integrate, and the rules are written in a model only that provider runs. For teams with data residency or sovereignty requirements, that deepens dependence on a single provider. An abstraction layer provided by a hyperscaler is not an abstraction layer.
Where Mia-Platform differs
- Rules that stay yours. Defined once, independent of any cloud, model or toolchain, so changing provider doesn't mean rewriting them.
- Enforced wherever agents run. Coding agents on developer laptops, agents in any cloud and in on-prem systems, under the same rules.
- One governance layer on top of every runtime. Keep the agent platforms you like: agents connect to one layer, whichever cloud they run on.
Hyperscaler Agent Platforms and Mia-Platform: where each approach is strong.
Read the rows that matter to your context. Where the category is as strong as we are, we say so.
| Criterion |  | Typical hyperscaler agent platforms |
|---|---|---|
| Governs agents wherever they run | Full The same rules for coding agents on developer laptops, agents in any cloud and on-prem systems. | Partial Strongest for agents connected to its own runtime and gateway; agents elsewhere need their own rules, and some are administered from the vendor's console. |
| Rules independent of the provider | Full Rules aren't written in any provider's policy model: change cloud or model, and they stay the same. | Partial Rules live in the provider's policy model and console, so changing provider means rewriting them; model vendors' admin controls cover their own agents only. |
| Integration effort across several clouds | Full Agents connect to one governance layer, whichever cloud they run on. | Partial Each cloud has its own identity, gateway and policy services to integrate, each with its own rule set. |
| Context shared across clouds | Full Context Catalog serves the same standards and knowledge to agents on every cloud, from one governed catalog. | Partial Memory and knowledge bases belong to each provider's runtime, so context is set up again on every cloud. |
| Enforcement depth inside one cloud | Partial Enforces at the call, across clouds; for agents on one provider's runtime, that provider's native policy engine goes deeper. | Full Deep enforcement for agents connected to its runtime and gateway: identity, policy engines, guardrails. |
| Managed runtime to build and run agents | Partial Mia-Platform runs on top of these runtimes: you choose where agents run and scale, and Mia-Platform decides what they may do. | Full Runtime, memory, scaling and evaluations, managed by the provider and ready to build on. |
Based on publicly available documentation and marketing materials. It describes what the category typically offers: individual products vary, so check each one against your own requirements.
The products behind this comparison.
Every Full row in the table comes from one of these products. Keep one set of rules across every cloud you use.
AI Foundry
Design, manage, and govern AI Playbooks to bring generative AI applications and agents to production.
Explore AI Foundry
Context Catalog
Connect, configure, and serve context to AI agents and applications through a governed catalog of enterprise knowledge.
Explore Context Catalog
Hyperscaler Agent Platforms: questions worth asking.
Three questions that cut through the positioning, and how we answer each one. They work for any vendor, including us.
Ask any vendor
With Mia-Platform, coding agents on laptops, in other clouds and on-prem systems are governed by the same rule set. A cloud's own governance is built around the agents connected to its runtime, while Mia-Platform applies the rules wherever the agent runs. See this row in the table
About Mia-Platform
Other categories you may be weighing.
Building on a hyperscaler runtime? Keep doing so. Mia-Platform runs on top of these runtimes. You choose where agents run; one rule set decides what they may do.
AI & MCP Gateways
Deep at the call. But a gateway alone doesn't know who the agent is, what it knows or what it may do in production.
DevOps Platforms
Mature pipeline governance inside their own toolchain. What happens to the agents that never touch it?
AI Governance Platforms
They hold the policy and the inventory. We apply the policy where agents act, and produce the evidence they consume.