Which AI gateway is best for enterprise teams? The one that fits your deployment rule, your identity stack and your provider contracts. If the gateway must run inside your own network, shortlist Kong AI Gateway, LiteLLM Enterprise, Bifrost Enterprise or TrueFoundry. If you are standardized on Azure, start with Azure API Management's AI gateway; on AWS, Amazon's own guidance deploys LiteLLM in your account. If runtime AI security is what drives the evaluation, Prisma AIRS AI Gateway, formerly Portkey. If you want a hosted control plane that runs only on the provider accounts you already hold and enforces dollar budgets at your negotiated rates before each call, with 0% markup on model spend, a BYOK control plane such as INFRO.
Below: what enterprises actually need from a gateway, a comparison table, each option described from its own pages as of October 2026, and when INFRO is not the right choice.
What does an enterprise need from an AI gateway?
An enterprise gateway is a control boundary, not a model menu. Six questions separate the options; the enterprise AI gateway checklist turns them into items to verify in a review.
- Where does it run? Inside your network, inside your cloud tenant, or hosted by the vendor. This is usually set by security policy before anyone compares features.
- Does it plug into your identity stack? SSO against your identity provider, SCIM so leavers lose access when the directory says so, and roles that separate who changes policy from who reads request data.
- Is every privileged change recorded? An audit log with actor and timestamp, and a retention period you can state to an auditor.
- Does spend control work on your own contracts? Enterprises already hold provider agreements with negotiated rates. Ask whether limits are in tokens or dollars, whether they use your rates, and whether they refuse before the provider is called or report afterwards.
- Does it fail over across providers? A second key on the same provider does not help when that provider is down.
- Can procurement buy it? Invoicing, contract terms, support commitments, and what is in place today versus on a roadmap.
Which AI gateways should enterprise teams compare?
| Gateway | Where it runs | SSO, roles, audit | Spend limits | Best when |
|---|---|---|---|---|
| Kong AI Gateway | Your data planes (self-hosted, cloud, Kubernetes), Konnect control plane, or fully self-hosted | Enterprise only | Token quotas and budgets; spend limits via AI Rate Limiting Advanced | You already run Kong for APIs |
| Prisma AIRS AI Gateway | Hosted; private cloud and VPC hosting on Enterprise | SSO and RBAC on Enterprise | Granular budgets and rate limits on Enterprise | Runtime AI security leads the evaluation |
| TrueFoundry | SaaS, hybrid, or self-hosted in your VPC, on-prem, air-gapped | SSO, RBAC and audit logging | Dollar budgets per day, week or month, 429 at the limit | You also want to deploy and serve models |
| LiteLLM Enterprise | Your cloud | SSO and SCIM, RBAC, audit logs | Budgets on virtual keys; spend by key, team, user, tag | You want the open-source default with a licence and support |
| Bifrost Enterprise | Self-hosted; in-VPC, on-prem or air-gapped on Enterprise | SSO, RBAC, audit on Enterprise | Budgets and rate limits in open source and Enterprise | You want an open-source gateway with an enterprise tier |
| Azure API Management | Your Azure tenant, including self-hosted gateways | Azure's own identity and policy | Tokens per minute and token quotas, not dollars | Your platform is Azure |
| AWS gateway guidance | Your AWS account (LiteLLM on ECS or EKS) | As LiteLLM provides | As LiteLLM provides | You are on AWS and will operate it yourself |
| Cloudflare AI Gateway | Cloudflare | Not covered by the pages read | Dollar spend limits, BYOK counted for priced models | You run on Cloudflare already |
| INFRO | Hosted; your cloud only under an enterprise agreement | SSO and SCIM on Business; roles and audit log on every plan | Dollar budgets at list or negotiated rates, before the call | You need spend control across your own provider accounts |
Which AI gateway is best if it must run inside your network?
Kong AI Gateway is the natural choice for a platform team that already runs Kong. It gives one API across providers including OpenAI, Anthropic, Azure AI, Amazon Bedrock and Gemini, load balancing, and automatic failover to another provider or model "when one is slow or unavailable"; guardrails for prompts and responses, PII sanitization, token quotas and budgets per consumer group, and MCP tooling1. Its data planes run self-hosted, in the cloud or on Kubernetes, managed through Konnect. Kong's pricing page marks RBAC, SSO and audit logging as "Enterprise only", lists AI Rate Limiting Advanced among the AI enterprise plugins, and says a fully self-hosted control and data plane is part of its separate Gateway Enterprise offering2.
LiteLLM Enterprise is the open-source LiteLLM gateway with a licence key. The base gateway exposes one OpenAI-compatible endpoint for over 100 providers, with virtual keys carrying models, budgets and rate limits, fallbacks and retries, guardrails, and deployment by Docker, Helm or Terraform against Postgres3. The licence adds SSO and SCIM, role-based access across organizations, teams and users, audit logs of admin actions and key changes "with retention policies your compliance team sets", and a dedicated support channel with optional 24/7 SLAs. LiteLLM states that it "runs in your cloud, so prompts and responses never leave your environment"4. Amazon's Guidance for Multi-Provider Generative AI Gateway on AWS deploys LiteLLM on ECS or EKS in your own account, with Bedrock models and external providers configured through LiteLLM's admin UI5; it is a reference deployment you operate, not a managed service.
Bifrost Enterprise builds on Maxim AI's open-source Bifrost. Budgets and rate limits are in the open-source edition; the Enterprise tier adds guardrails, SSO via SAML and OIDC, role-based access with custom roles, audit trails, clustering for high availability, and deployment "in air-gapped environments - on-prem, in-VPC, or hybrid". The pricing page describes no hosted offering6.
TrueFoundry describes itself as "The Enterprise AI Gateway for LLMs, MCPs & Agents" and runs in "VPC, on-prem, air-gapped, or across multiple clouds", with SSO, RBAC and audit logging listed as governance features7. Its gateway documentation says it "can be used as a standalone solution", with routing by weight, latency or priority, guardrails including prompt injection, an MCP gateway, and deployment as SaaS, hybrid or self-hosted8. Budgets are set in dollars per day, week or month and return 429 when exceeded, with an audit mode that observes without blocking9. It is the stronger pick when the same team also deploys and serves its own models.
Which AI gateway is best for teams standardized on Azure or AWS?
Azure API Management's AI gateway is a set of capabilities inside API Management, "not a separate offering". It manages models in Microsoft Foundry "or non-Microsoft providers such as Amazon Bedrock", offers a unified OpenAI-compatible model API in preview, load balancing and circuit breakers across backends, Azure AI Content Safety on prompts, semantic caching with Azure Managed Redis, and token metrics per consumer10. Its limit is llm-token-limit: tokens per minute or a token quota per counter key, 429 or 403 when exceeded. It "counts prompt and completion tokens only", and Microsoft notes that concurrent requests "can temporarily exceed the configured token limit"11. If your governance already lives in API Management, this is the shortest path; if finance asks for limits in dollars, you will translate tokens to money yourself.
On AWS, the published guidance above is the documented route; it inherits LiteLLM's features and puts its operation on your team.
Which AI gateway is best when runtime AI security leads?
Prisma AIRS AI Gateway is what Portkey's hosted gateway became under Palo Alto Networks; Portkey's pricing page reads "Portkey is now PRISMA AIRS AI Gateway, generally available for all enterprises". Its Enterprise tier lists SSO, role-based access control, granular budgets and rate limits, private cloud deployment, VPC hosting, data isolation and custom retention for logs and metrics12. If what models receive and return is the first question in your security review, start here. Kong's prompt and response guards are the alternative for Kong shops.
What about Cloudflare AI Gateway for an enterprise?
Cloudflare AI Gateway suits teams that already run on Cloudflare. Its analytics, caching and rate limiting are free, with guardrails billed as Workers AI inference13. Spend limits are dollar budgets by provider, model or metadata, checked before the provider is called, that apply to your own keys "for models with known pricing". Cloudflare is candid that costs are estimates and that enforcement is eventually consistent, so a burst can briefly pass a limit14. The pages read for this guide do not cover SSO, roles or audit for AI Gateway, so verify those against your account.
INFRO, and when it is not the right choice
INFRO is a hosted AI gateway and control plane that runs only on the provider accounts you connect. Your providers keep billing you directly under your own contracts; INFRO charges a software subscription, with 0% markup on model spend. For an enterprise that means:
- Identity and access: SAML and OIDC single sign-on and SCIM 2.0 provisioning from the Business plan, with a domain proved by DNS first; owner, admin, developer and analyst roles; members confined to chosen projects; two-factor and passkeys on every plan.
- Audit: member, key and policy changes recorded with actor and timestamp on every plan; request logs kept 7 to 90 days by plan, with prompt and completion logging off by default.
- Spend on your own contracts: budgets per organization, project, member and key, checked before the provider is called; estimated provider cost at list rates or the negotiated rates you enter (from Team); on Business, the estimate compared daily with OpenAI's and Anthropic's own cost APIs. Estimated provider cost and INFRO's subscription are always reported separately.
- Reliability and policy: routing and failover across your providers, model allowlists per project, keys limited by provider or IP range and rotated with an overlap window, guardrails on Business, and a management API for configuration as code.
- Procurement: Business is $599 a month with unlimited seats and projects; an enterprise agreement adds invoicing, custom volume and retention, named support, and self-hosted or hybrid deployment scoped per contract. See INFRO for enterprise.
It is not the right choice if prompts must stay inside your network today without negotiating an agreement (use Kong, LiteLLM Enterprise, Bifrost Enterprise or TrueFoundry), if you need regional processing pinned to one region (INFRO does not offer it), if you need a published SLA before signing (INFRO agrees one per contract and publishes none), if your governance is already built in Azure API Management, or if you also need to host and fine-tune models (TrueFoundry).
How should an enterprise choose an AI gateway?
- Write down the deployment rule and strike every option that cannot meet it.
- Confirm SSO, SCIM, roles and audit are in the plan you would buy, not only in the top tier you were demoed.
- Ask each vendor whether limits are in tokens or dollars, whose rates they use, and whether they refuse before the call.
- Fail one provider on purpose during the trial and watch where traffic goes.
- Ask procurement's questions early: invoicing, terms, support, and what is roadmap. The comparison hub has side-by-side pages for most of these products.
Summary
There is no single best enterprise AI gateway. Teams that must run the gateway in their own network have Kong, LiteLLM Enterprise, Bifrost Enterprise and TrueFoundry; Azure shops have API Management; security-first buyers have Prisma AIRS; and enterprises that want a hosted control plane governing spend and access across the provider contracts they already hold, with 0% markup on model spend, have BYOK control planes such as INFRO.