Managed API vs Azure AI platform

KeepRouter vs Microsoft Foundry, formerly Azure AI Foundry

KeepRouter fits teams that want a managed model API with KeepRouter credentials and a bounded public catalog. Microsoft Foundry, formerly Azure AI Foundry, is an Azure platform for models, agents, tools, projects, evaluation, tracing, monitoring, and enterprise policy. Foundry has several endpoint families, so an OpenAI SDK example should not be read as one universal endpoint for every workload. [1] [2] [6] [7]

Last reviewed 2026-08-15 · Editorial review: KeepRouter Editorial

Short answer

Choose KeepRouter when the application needs managed access to a documented model and does not need Azure resource deployment or Entra-based platform governance. Choose Microsoft Foundry when Azure projects, role-based access, networking, policies, model deployments, agents, evaluation, tracing, and monitoring belong in the same operating boundary. Microsoft Foundry is the current name for the product previously called Azure AI Foundry. Its SDK guide documents multiple endpoints, including project endpoints, an OpenAI-compatible /openai/v1 endpoint, Anthropic endpoints, and tool endpoints. Those routes have different jobs and should not be flattened into one compatibility claim.

The category difference is large. KeepRouter sells a managed model API and prepaid usage through its own account. Foundry is an Azure PaaS that organizes models and agents under Azure resources and projects. The correct choice depends on whether Azure control is a requirement or overhead.

Decision table

Decision	KeepRouter	Microsoft Foundry
Resource model	KeepRouter account, API key, live catalog, and documented route	Azure subscription, Foundry resource, projects, deployments, roles, and service endpoints
Client surface	OpenAI or Anthropic compatible routes where the selected model page documents them, plus other documented APIs	Foundry SDK project endpoint, OpenAI-compatible endpoint, Anthropic SDK endpoint, and tool APIs for their respective workloads
Model lifecycle	Use models exposed by the current KeepRouter catalog	Discover, deploy, operate, evaluate, and govern models within the Foundry resource model
Agents and tools	Application-owned unless another public KeepRouter route states otherwise	Agent Service, project tools, knowledge integrations, tracing, and monitoring are part of the platform
Identity and policy	Scoped KeepRouter keys and KeepRouter public security contract	Azure RBAC, Microsoft Entra identity, networking, Azure Policy, and resource governance where supported
Billing	KeepRouter prepaid ledger and public customer pricing	Each Foundry model or service can have its own Azure billing unit, offer, region, and deployment rule

Endpoint choice is part of the architecture

The official Foundry SDK page distinguishes a project endpoint from direct model endpoints. The project endpoint is used with Foundry SDK clients and project resources. The /openai/v1 endpoint provides the broadest OpenAI SDK compatibility for supported Azure OpenAI style operations, including embeddings. Anthropic models can use an Anthropic SDK endpoint. Tools have their own APIs.

That distinction matters during migration. A team that only checks chat text through an OpenAI client has not verified embeddings, agent state, project tools, deployment names, streaming events, authentication, or quota behavior. The Foundry quickstart itself requires a deployed model and a project endpoint before it creates a model response and an agent conversation.

KeepRouter is suitable when Azure is not the product requirement

KeepRouter reduces the setup to a KeepRouter account, prepaid credit, a scoped key, and an exact model route from the live catalog. It can be a practical fit for applications that run outside Azure, teams that do not want to provision model deployments, or services whose organization policy does not require Azure ownership.

KeepRouter does not reproduce Foundry projects, Microsoft Entra identity, Azure networking, policy, deployment controls, hosted agents, evaluation, tracing, or monitoring. If those are acceptance criteria, replacing Foundry with a model API would remove required controls rather than simplify them.

Foundry is suitable when Azure owns the workload

Foundry fits organizations already using Azure for identity, network boundaries, resource policy, cost management, and operations. It gives model builders and application developers a shared resource and project structure. Models, agents, tools, evaluation, and observability can live under the same Azure governance model.

That platform brings deployment work. A model must be available under the chosen offer and region, then deployed with the required quota. Endpoint, API version, deployment name, authentication method, and SDK must match. The pricing page also separates Models, Agent Service, knowledge and tools, observability and trust, and local or edge products. A single token price cannot represent the whole platform.

Capability boundary

OpenAI compatibility in Foundry is route-specific. It does not mean every Foundry model, agent, tool, or project operation accepts the same OpenAI request. The official SDK guide should decide which client and endpoint to use. The same caution applies to KeepRouter: its OpenAI and Anthropic compatible routes cover documented models and operations, not every native provider or Azure field.

Model semantics also remain separate. Even when two routes accept similar JSON, tool schemas, structured output, reasoning controls, safety behavior, stream chunks, token accounting, and errors can differ. Migration tests must use the exact deployment candidate.

Move from Foundry to KeepRouter

Record the Foundry resource, project endpoint, direct model endpoint, deployment name, SDK, authentication method, tools, agent state, and evaluation or tracing dependencies.
Isolate calls that are plain model inference. Project operations, hosted agents, Azure tools, RBAC, and monitoring do not move through a base URL change.
Select the exact KeepRouter model ID and route from the live catalog. Remove Azure deployment names and API fields that are not in the KeepRouter OpenAPI contract.
Replace Azure credentials with a scoped KeepRouter key, then test chat, Responses, Messages, embeddings, streaming, and tools only where the target route documents them.
Reconcile usage and errors against the KeepRouter ledger before deleting Azure deployments or monitoring rules.

Move from KeepRouter to Foundry

Decide whether the workload needs a direct /openai/v1 model endpoint, an Anthropic endpoint, a Foundry project endpoint, or a hosted agent.
Create the Azure subscription resources and project, deploy the model in a supported region, assign least-privilege roles, and confirm quota.
Map every KeepRouter public ID to the Foundry deployment name and exact model version. KeepRouter's upstream mapping and credit balance do not transfer.
Update authentication and client construction, then add Azure logging, tracing, budget ownership, networking, and policy deliberately.
Run failure tests for deployment not found, quota exhaustion, authorization, streaming cancellation, tool errors, and regional constraints before switching traffic.

Use best AI gateways to compare product categories and managed versus self-hosted gateways to place operating responsibility. The evaluation guide provides a neutral acceptance checklist.

Frequently asked questions

Is Azure AI Foundry now called Microsoft Foundry?

Yes. Current Microsoft documentation uses Microsoft Foundry and notes Azure AI Foundry and Azure AI Studio as former names.

Can an OpenAI SDK call Microsoft Foundry?

Yes for supported operations through the documented /openai/v1 endpoint. Project, Anthropic, tool, and agent operations can require different clients or endpoints.

Does the Foundry project endpoint handle every model operation?

No. Microsoft documents separate endpoint families. Use the SDK overview to select the project, direct OpenAI, Anthropic, or tool endpoint required by the workload.

Does KeepRouter replace Azure identity and policy?

No. KeepRouter has its own key and service contract. Azure RBAC, Entra identity, networking, policy, and resource governance remain Microsoft Foundry responsibilities.

Can I compare one advertised token price?

That is insufficient for a platform decision. Compare the exact model deployment and include any agent, tool, evaluation, monitoring, networking, and operational costs your design actually uses.

Sources reviewed

Sources last reviewed 2026-08-15