9 Best AI Gateways for Multi-Tenant SaaS Products

A guide to choosing the right AI gateway for isolating tenants, managing costs, and enforcing security in multi-tenant SaaS applications. This comparison reviews top solutions like Bifrost, LiteLLM, and Kong, ranking the best options for performance, governance, and scalability.

Adding generative AI features to a multi-tenant SaaS product introduces significant architectural challenges. Unlike traditional software, where costs are relatively fixed, AI features incur variable, per-token costs driven directly by tenant usage. Without a control plane to manage this, a single tenant could generate a massive, unexpected bill, eroding margins or causing service disruptions. An AI gateway is the essential infrastructure for solving this problem, providing the necessary layer for tenant isolation, cost control, and security.

A generic API gateway is not sufficient for AI workloads. An AI gateway understands token-based billing, handles streaming responses, and provides specialized features like semantic caching and provider-specific health checks. For a multi-tenant SaaS platform, the gateway must also provide robust mechanisms for isolating tenant data, managing per-tenant API keys, enforcing tenant-specific budgets and rate limits, and attributing costs accurately.

This article evaluates the top nine AI gateways available today, focusing on their suitability for multi-tenant SaaS applications. The analysis covers open-source and managed solutions, assessing them on criteria crucial for building scalable, secure, and profitable AI-powered products.

Key Criteria for Evaluating Multi-Tenant AI Gateways

When selecting a gateway, SaaS providers should look for specific features that support tenant isolation and management:

• Virtual & Per-Tenant Keys: The ability to issue unique, scoped API keys for each tenant without exposing root provider credentials. This is the foundation of multi-tenant security and usage tracking.
• Tenant-Level Budgets & Rate Limits: Enforcing spending limits and request quotas on a per-tenant basis to prevent cost overruns and ensure fair resource allocation.
• Cost & Usage Attribution: Granular tracking of token consumption and costs for each tenant, enabling accurate billing and profitability analysis.
• Data Isolation: Ensuring that data from one tenant, such as in-flight requests or cached responses, is never exposed to another.
• Custom Routing & Policies: The flexibility to apply different model routing rules, guardrails, or provider access policies to different tenants or pricing tiers.
• Scalability & Performance: The ability to handle high request volumes with minimal latency, ensuring a responsive user experience as the tenant base grows.

The 9 Best AI Gateways for SaaS

Here are the top AI gateways ranked for multi-tenant SaaS use cases, based on their feature sets, scalability, and enterprise readiness.

1. Bifrost

Bifrost is a high-performance, open-source AI gateway from Maxim AI, written in Go. It is designed for enterprise-grade scale and governance, making it a leading choice for multi-tenant applications. Its core strength lies in its granular, hierarchical governance model and extremely low latency.

Bifrost's architecture is built around Virtual Keys, which are the primary mechanism for multi-tenant isolation. A SaaS platform can generate a unique virtual key for each tenant, project, or even end-user. Each key can be configured with its own budget, rate limits, model access policies, and routing rules. This allows a provider to offer different service tiers (e.g., Free, Pro, Enterprise) with distinct usage caps and model access, all managed from a single gateway instance.

Best for: Enterprise SaaS platforms and regulated industries that require best-in-class performance, comprehensive governance, and flexible deployment options (cloud, VPC, or on-premises).

Key Multi-Tenant Features:

• Virtual Keys: Scoped API keys that isolate tenants completely. Keys can be created and managed programmatically via API.
• Hierarchical Budgets: Set and enforce spending limits at the tenant, team, or user level.
• Access Profiles: Create reusable policies (e.g., "Pro Tier") that bundle provider access, models, and limits, which can then be applied to new tenants automatically.
• Enterprise-Grade Security: Central to Bifrost’s design is its robust security and governance framework. Beyond routing, Bifrost applies governance and security controls centrally, and Bifrost Edge extends that same governance and security to AI traffic on employee machines, with endpoint enforcement on each device.
• Low Latency: Published benchmarks show an overhead of just 11 microseconds per request, ensuring that the gateway is not a bottleneck.
• Deployment Flexibility: Can be deployed as a managed service, in a VPC, or fully on-premises, providing full data control.

2. LiteLLM

LiteLLM is a popular open-source Python library and proxy that provides a unified API for over 100 LLM providers. It has gained significant traction for its ease of use and extensive model support. Its multi-tenancy features are centered around virtual keys and a hierarchical structure of "Teams" and "Organizations".

SaaS platforms can use LiteLLM to assign a virtual key to each tenant, with associated budgets and user management. The "Teams" feature, available in the open-source version, allows for grouping users and keys under a single policy set. This model provides a solid foundation for tenant management in many applications.

Best for: Teams looking for a flexible, open-source solution with the widest range of model support and a straightforward path to implementing basic multi-tenancy.

Key Multi-Tenant Features:

• Virtual API Keys: Assign unique keys to tenants for usage tracking and management.
• Teams & Organizations: Group keys and users to manage policies and track spend collectively.
• Per-Key/Team Budgets: Set spending limits that apply to specific tenants or groups.
• UI for Management: Provides a user interface for managing keys, teams, and viewing analytics.

3. Kong AI Gateway

Kong AI Gateway extends the widely-used Kong API Gateway with specific capabilities for AI workloads. Its multi-tenancy model is inherited from Kong's mature "Consumer" and "Consumer Group" concepts. Each tenant can be represented as a Consumer Group, allowing policies like rate limiting, prompt validation, and credential management to be applied on a per-tenant basis.

Kong's strength is its robust, battle-tested core and its plugin-based architecture, which allows for extensive customization. For AI, it offers plugins for token-based rate limiting, prompt engineering, and connecting to various LLM providers.

Best for: Organizations already invested in the Kong ecosystem or those who need a highly customizable, enterprise-grade API management solution for both AI and traditional microservices.

Key Multi-Tenant Features:

• Consumers & Consumer Groups: A mature model for isolating tenants and applying policies.
• Token-Based Rate Limiting: Enforce limits based on token consumption, which is critical for cost control.
• Plugin Architecture: Apply different AI-related plugins (e.g., prompt templates, guardrails) to different tenant groups.
• Unified Observability: AI metrics are tagged with consumer labels, enabling clear tenant attribution in logs and dashboards.

4. Cloudflare AI Gateway

Cloudflare AI Gateway is a managed service that provides observability, caching, and routing for AI applications. As part of Cloudflare's global network, its key advantage is performance and ease of setup. For multi-tenancy, it allows developers to attach custom metadata, such as a tenant_id, to requests. This metadata flows through to logs and analytics, enabling usage tracking per tenant.

While its tenant management features are less explicit than those of Bifrost or Kong, its logging and analytics capabilities provide the necessary data for a SaaS platform to implement its own usage tracking and billing logic.

Best for: Applications already on the Cloudflare ecosystem or those prioritizing ease of use, global low latency, and built-in caching.

Key Multi-Tenant Features:

• Custom Metadata: Tag requests with tenant identifiers for downstream analytics.
• Analytics and Logging: A powerful dashboard to view usage, costs, and errors, which can be filtered by custom metadata.
• Per-Gateway Rate Limiting: Apply rate limits to a gateway endpoint, which can be used to manage tenants collectively.
• Tenant-Isolated Caching: Caching is a key feature, which can help reduce costs and latency for tenants with repetitive queries.

5. OpenRouter

OpenRouter provides a unified API to a vast catalog of models from dozens of providers, positioning itself as a "marketplace for LLMs." Its multi-tenancy support is straightforward: a SaaS provider can generate a unique API key for each of its customers. Each key can have its own credit limit, which resets on a configurable schedule (daily, weekly, monthly).

This key-based approach is simple and effective for many SaaS use cases, allowing for direct cost control and usage monitoring per tenant.

Best for: Startups and SaaS products that need quick access to the widest variety of models and a simple, pay-as-you-go approach to tenant cost management.

Key Multi-Tenant Features:

• Per-Customer API Keys: The primary mechanism for tenant separation.
• Credit Limits: Set hard spending caps on a per-key basis.
• Unified Billing: Simplifies accounting by consolidating all model costs into a single bill.
• Bring Your Own Key (BYOK): Allows larger tenants to use their own provider accounts and committed-use discounts while still benefiting from OpenRouter's routing layer.

6. Azure API Management

Azure API Management (APIM) is a powerful, general-purpose API gateway that can be configured to manage AI workloads. Microsoft provides guidance and pre-built policies for using APIM as an AI gateway, covering challenges like token-based cost management and routing. For multi-tenancy, APIM uses a concept of "Products" and "Subscriptions." A SaaS provider can define different products (e.g., service tiers) and issue unique subscription keys to each tenant, enabling per-tenant policies and analytics.

Best for: Organizations heavily invested in the Microsoft Azure ecosystem, especially those using Azure OpenAI.

Key Multi-Tenant Features:

• Products and Subscriptions: A flexible model for grouping APIs and managing tenant access.
• Policy Engine: Use policies to implement custom logic, such as validating a tenant's JWT or routing to a tenant-specific backend.
• Cost and Quota Management: Enforce token-based quotas and track usage per subscription key.
• Native Azure Integration: Deep integration with Azure services like Entra ID for authentication and Azure Monitor for logging.

7. AWS API Gateway

Similar to Azure's offering, AWS API Gateway is a managed service for creating and managing APIs. While not an AI-specific gateway out of the box, AWS provides reference architectures for building a multi-tenant generative AI gateway using API Gateway, Lambda, and other AWS services. This approach uses API keys and usage plans to manage tenant access, throttling, and quotas.

This solution requires more assembly than a dedicated AI gateway but offers deep integration with the AWS ecosystem, including services like Amazon Bedrock.

Best for: Teams with strong AWS expertise who want to build a custom AI control plane using native AWS services.

Key Multi-Tenant Features:

• Usage Plans & API Keys: AWS's standard mechanism for managing access and throttling for different tenants.
• Lambda Authorizers: Implement custom authentication and authorization logic on a per-tenant basis.
• Integration with AWS Services: Seamlessly connect to Amazon Bedrock, SageMaker, and logging/monitoring tools like CloudWatch.
• Account Sharding: For strict isolation, tenants or lines of business can be deployed into separate AWS accounts.

8. Apigee (Google Cloud)

Apigee, Google Cloud's API management platform, functions as an enterprise-grade gateway that can be tailored for AI. It provides robust security, traffic management, and analytics. For multi-tenancy, Apigee uses "API Products," which bundle resources and policies, and "Developer Apps," which represent the tenants consuming those products. Each app gets a unique API key, enabling per-tenant policy enforcement and analytics.

Best for: Large enterprises, particularly those using Google Cloud and Vertex AI, that need a comprehensive API management solution with strong governance and analytics capabilities.

Key Multi-Tenant Features:

• API Products and Developer Apps: A structured approach to defining service tiers and onboarding tenants.
• Conditional Routing: Use policies to route requests to different backends based on tenant ID or other attributes.
• Spike Arrest and Quotas: Protect backend services and manage costs by enforcing per-tenant traffic limits.
• Extensive Analytics: Capture detailed usage data for each tenant, which can be exported for billing and analysis.

9. MLflow AI Gateway

Part of the open-source MLflow platform, the MLflow AI Gateway is designed to provide a lightweight, unified interface for multiple LLM providers. It is configured via a simple YAML file where routes to different models are defined. While its multi-tenancy features are not as extensive as dedicated gateways, it provides centralized API key management and per-route rate limiting.

This makes it a viable option for internal platforms or smaller-scale SaaS products where multiple teams act as tenants.

Best for: Data science and ML teams already using the MLflow ecosystem who need a simple, self-hosted gateway to standardize model access.

Key Multi-Tenant Features:

• Centralized Key Management: Securely stores provider keys, avoiding the need to distribute them to tenant applications.
• Route-Based Configuration: Can define different routes for different tenants or use cases.
• Rate Limiting: Apply basic requests-per-minute limits to specific routes.

Conclusion

Choosing the right AI gateway is a critical architectural decision for any multi-tenant SaaS product. The gateway serves as the control plane for managing costs, ensuring security, and maintaining reliability.

For SaaS platforms requiring high performance, granular per-tenant control, and enterprise-grade security, Bifrost stands out as the top choice due to its purpose-built architecture for hierarchical governance. For teams prioritizing the broadest model support in an open-source package, LiteLLM offers a flexible and comprehensive solution. Managed services like Cloudflare AI Gateway and OpenRouter provide simplicity and speed, while the offerings from major cloud providers (Azure, AWS, Google) deliver deep ecosystem integration for teams willing to build a more custom solution.

The best choice depends on your specific requirements for control, scalability, and existing infrastructure. Teams evaluating these options can request a Bifrost demo or review its open-source repository to explore its capabilities further.

Sources

• Guidance for a Multi-Tenant, Generative AI Gateway with Cost and Usage Tracking on AWS
• Multi-Tenant Architecture with LiteLLM
• Use Azure API Management in a Multitenant Solution - Microsoft Learn
• AI Gateway Series #2 — Organization, Team Management & Multi-tenancy - Truefoundry
• Overview · Cloudflare AI Gateway docs