A Sovereign Azure API Management Alternative
Azure API Management's AI gateway governs Azure model traffic well, from inside Azure. The Scrydon AI Gateway governs any model from inside your perimeter — air-gapped, on-premises, sovereign cloud or Azure — with every call running as a person.
If your estate is Azure and stays there, Azure API Management is the natural gateway in front of Azure OpenAI: token limits, token metrics, caching, load balancing, all as policies you already know. The Scrydon AI Gateway is for the organisation whose models, developers and obligations do not all live in one hyperscaler: one governed endpoint for any model, every call attributed to a person, deployed where your production runs. It stands alone and can be deployed on its own.
Read this if you're an architect in a public body or regulated enterprise weighing an Azure-native gateway against a control point the organisation owns, wherever it runs.
Deploy the AI Gateway Starts at €500 / month on a yearly commitment, deployed on its own in a day.
The Scrydon AI Gateway is a sovereign alternative to Azure API Management's AI gateway: a single governed endpoint that speaks the standard model APIs — Anthropic Messages, OpenAI Chat Completions, OpenAI Responses and Gemini — so existing tools reach any model unchanged, where every call runs under the caller's own federated identity, against a clearance-gated model allowlist, with data loss prevention, a spend cap and an immutable audit trail. It shares one policy and one audit chain with governed tool calls and sandbox egress, and runs air-gapped, on-premises, on a European sovereign cloud or on Azure and Azure Local.
Azure API Management has grown a capable AI gateway: policies that cap tokens per subscription, emit token metrics to Azure Monitor, cache semantically similar prompts, balance load across Azure OpenAI deployments and apply content safety — with a self-hosted gateway for hybrid estates. For an organisation whose models are Azure OpenAI and whose developers hold Azure subscriptions, it is a sensible answer. Its limits are structural rather than technical. It is a hyperscaler's control plane, which a sovereignty test on jurisdiction, keys and disconnected operation does not pass; a consumer is an API subscription, so attribution stops at the subscription; models outside Azure are a configuration exercise rather than the point; and governance ends at the API boundary while an agent's day is mostly tool calls. The Scrydon AI Gateway keeps the same developer experience — the standard APIs, unchanged tools — and moves the control point into your perimeter: a gateway key minted against a named person in your identity provider, any model by name, one policy and one audit chain across the model call, the tools the agent calls and the network its sandbox may reach. It runs on Azure and Azure Local too, which is often where the comparison ends up.
Runs as a Person, Not a Subscription
Every call resolves through your identity provider to the human who made it, with their delegated grants — the basis for per-developer cost, clearance-gated models and revocation on the next turn.
Any Model, Any Perimeter
Frontier APIs, models in your cloud tenancy and open-weight models on your own hardware, behind one endpoint — deployed air-gapped, on-premises, on a European sovereign cloud or on Azure.
Governance Past the API Boundary
One policy and one audit chain across the model call, the tools the agent calls over MCP, and the egress of the sandbox those tools run in.
Azure API Management Alternative in the Scrydon platform
One integrated, sovereign architecture. Here is where Azure API Management Alternative sits — highlighted against the full stack it works with.
The AI OS for Humans & AI Agents
Ontology & Semantic Layer, one connected model for your data, knowledge & processes
Combining the best of data lakes, data warehouses and search
Governed access to every model, and the agents & workflows that execute across your systems
Integrate across A2A, MCP, legacy systems and data sources
Secure domain federation, trusted data sharing, and cross-boundary intelligence
Sovereign Foundations
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What Azure API Management governs, and what the AI Gateway governs from your perimeter
Azure API Management's strength is that it is already there: an API gateway most Azure estates run, with AI policies added for token limits, token metrics, semantic caching, load balancing across Azure OpenAI deployments and content safety, all in the policy language its administrators know. The Scrydon AI Gateway takes the same governed-address idea and moves the control point into your perimeter: the call runs as a named person from your identity provider rather than as a subscription, any model is reached by name, data loss prevention screens what leaves, and the audit record settles before the stream finishes. It runs air-gapped, on-premises, on a European sovereign cloud, or on Azure and Azure Local.
The standard APIs, unchanged tools — Both put a governed address in front of your models. The AI Gateway speaks the Anthropic, OpenAI and Gemini dialects natively, so coding agents and applications run through it without modification.
A person, not a subscription — API Management attributes traffic to an API subscription or a validated token. The AI Gateway mints keys against a named person in your identity provider and uses that person's delegated grants when the agent goes on to call a tool.
Any model, by name — Azure OpenAI and Azure AI models, other vendors' APIs, and open-weight models on your own hardware are reached through the same endpoint and swapped by configuration, never silently substituted.
Your perimeter, including disconnected — The AI Gateway runs air-gapped, on-premises, on a European sovereign cloud, or on Azure and Azure Local — the same cluster, the same policy, wherever the sovereignty tests point.
When the gateway has to pass the same tests as the workload
Azure API Management is a fair choice when the models are Azure OpenAI, the developers hold Azure subscriptions and the estate is staying in Azure. The gap opens when the gateway is asked to pass the same tests as the workload. A public body or regulated enterprise that has answered the sovereignty questions — whose jurisdiction, whose keys, what happens disconnected, how do we exit — cannot answer them differently for the control point that sees every prompt. Nor can a subscription tell an auditor which person made a call, or what their agent did next against systems the gateway never sees. The Scrydon AI Gateway is built for that organisation: every call attributable to a person, one policy and one audit chain across the model call, the tools the agent calls and the sandbox it runs in, deployed wherever the tests point — including Azure — and deployable on its own before anything else is.
Scrydon AI Gateway vs Azure API Management (AI gateway)
Both put model traffic behind a governed address and both meter tokens. The difference is where the control point lives, who a call runs as, and how far the governance reaches once the model has answered.
| Capability | Scrydon | Azure API Management |
|---|---|---|
| Who the call runs as | The person, resolved through your identity provider, with their own delegated grants | An API subscription, or a validated token; attribution per subscription or product |
| Models behind it | Frontier APIs, your cloud tenancy, open-weight on your own hardware — by name, swapped by configuration | Azure OpenAI and Azure AI models first; other backends by configuration |
| Model calls governed | Clearance-gated allowlist, DLP, moderation, cap and immutable audit on every call | Token limits and quotas per subscription, content safety, caching, logging to Azure Monitor |
| Tool calls governed | Same identity, policy and audit chain as the model call | Any HTTP API can be fronted; not the caller's delegated grants in a sandbox |
| Network egress from the sandbox | Enforced outside the workload, which cannot reconfigure it | Out of scope |
| Where the vendor key lives | On the platform; never issued to a developer | Managed identity to Azure OpenAI; other credentials held in the gateway |
| Cost attribution | Per person, per team or unit, and per turn, by model, capability and workflow, with an on-pace projection and a cap | Token metrics per subscription and dimension, in Azure Monitor |
| Deployment & sovereignty | Sovereign — air-gapped, on-premises, European cloud, or Azure and Azure Local | Azure-hosted control plane; a self-hosted gateway for hybrid |
| Pricing model | Fixed monthly fee for the cluster that carries your people, excluding hosting | Azure service tiers, billed by the hour, plus the model consumption |
A category comparison, written to orient: Azure API Management is a mature product and we would not pretend otherwise — Scrydon itself runs on Azure and Azure Local for customers who choose it. Azure and Azure API Management are trademarks of Microsoft; capabilities evolve — verify current details with the vendor.
Frequently asked questions
What is the best alternative to Azure API Management as an AI gateway?+
How is the Scrydon AI Gateway different from Azure API Management's AI gateway?+
Can the AI Gateway run on Azure?+
Does the AI Gateway support Azure OpenAI and Azure AI models?+
Can we start with just the AI Gateway?+
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