Best Air-Gapped & On-Prem AI Gateways for Regulated Industries

This guide evaluates top AI gateways that offer air-gapped and on-premise deployments, a critical requirement for healthcare, finance, and government. Bifrost emerges as a leading option for its performance, comprehensive governance, and deployment flexibility inside private networks.

For organizations in regulated industries like healthcare, financial services, and the public sector, adopting AI introduces a significant compliance challenge: how to leverage powerful large language models (LLMs) without sending sensitive data to third-party cloud services. Standard SaaS AI platforms that process data externally are often non-starters. The solution is an on-premise or air-gapped AI gateway that runs entirely inside the organization's network perimeter, ensuring data sovereignty and control. Bifrost, an open-source AI gateway from Maxim AI, is designed for these high-stakes environments.

An air-gapped deployment means the system operates on a network that is physically isolated from the public internet. This architecture is the gold standard for security in government and critical infrastructure. For many regulated commercial entities, a private cloud (in-VPC) or on-premise deployment provides a similar level of control, keeping all data processing within the organization's security boundary. This guide compares the leading AI gateways that support these deployment models.

Key Evaluation Criteria for On-Premise AI Gateways

When selecting an AI gateway for a regulated environment, the evaluation criteria extend beyond simple API unification.

• Deployment Flexibility: The gateway must support true on-premise, in-VPC, or fully air-gapped installations. This is non-negotiable for maintaining data residency and control.
• Security and Compliance: The platform needs robust security features, including integration with enterprise identity providers (SSO/OIDC), role-based access control (RBAC), and secrets management (e.g., HashiCorp Vault).
• Auditability: Every request, response, and configuration change must be logged in immutable, tamper-evident audit trails to satisfy compliance requirements from bodies like HIPAA, FINRA, and government agencies.
• Data Governance: The gateway must be able to enforce policies on the data itself, such as redacting personally identifiable information (PII) or protected health information (PHI) before a prompt reaches an LLM.
• Performance: The gateway should introduce minimal latency, as it sits in the critical path of every AI request. High-throughput and low-overhead are essential for production workloads.

Top AI Gateways for Air-Gapped and On-Premise Use

Here is a comparison of AI gateways that offer self-hosted deployment models suitable for regulated industries, with an analysis of their strengths and weaknesses.

1. Bifrost by Maxim AI

Bifrost is a high-performance, open-source AI gateway written in Go. It is purpose-built for enterprise-grade deployments where performance, security, and deployment flexibility are paramount.

• Best for: Enterprises in regulated industries needing a high-throughput, low-latency gateway with comprehensive governance and full deployment sovereignty. Its support for air-gapped, in-VPC, and on-premise installations makes it a top choice for healthcare and financial services.

Key Features:

• Deployment: Bifrost Enterprise offers multiple deployment options, including as a single binary, in a Docker container, or via a Helm chart for Kubernetes. Its architecture fully supports in-VPC, on-premise, and air-gapped environments, ensuring no data leaves the network boundary.
• Performance: Adds only 11 microseconds of overhead at 5,000 requests per second, making it suitable for latency-sensitive applications.
• Governance and Security: Provides enterprise-grade features including high-availability clustering, user provisioning via OIDC with providers like Okta and Entra, and immutable audit logs for SOC 2, HIPAA, and ISO 27001 compliance.
• Endpoint Governance: A key differentiator is Bifrost Edge, which extends the gateway's security and governance policies to employee machines. This ensures that even AI tools used on desktops are routed through the secure, audited gateway, preventing data leakage from "shadow AI" usage. Policies are managed centrally, and Bifrost Edge enforces them on the endpoint.

2. Kong AI Gateway

Kong AI Gateway extends Kong's popular open-source API gateway with features specifically for managing AI traffic. It allows organizations to leverage their existing Kong infrastructure for LLM governance.

• Best for: Organizations already invested in the Kong ecosystem that need to add AI-specific controls like prompt engineering and cost management to their existing API management strategy.

Key Features:

• Deployment: Kong can be deployed on-premise, in the cloud, or in a hybrid model. Its flexible architecture allows it to run within an organization's data center or private cloud.
• AI-Specific Plugins: Offers a suite of plugins for AI workloads, including prompt templating, PII redaction, and routing to various LLM providers.
• Observability: Integrates with tools like Prometheus and Grafana for monitoring and provides detailed analytics on token usage and request latency.
• Ecosystem: As a mature API gateway, it benefits from a large community and a wide range of plugins for authentication, security, and traffic control.

3. LiteLLM

LiteLLM is an open-source Python library and proxy server that provides a unified interface for over 100 LLM providers. Its primary focus is on simplifying access to a wide variety of models.

• Best for: Python-centric teams and organizations that need a flexible, open-source tool to manage access to a diverse set of LLMs and require a self-hosted solution for compliance.

Key Features:

• Deployment: LiteLLM can be self-hosted as a Docker container or directly on a server, enabling on-premise and private cloud deployments.
• Provider Support: Its main strength is the sheer number of supported LLM providers, all accessible through a single, consistent API.
• Cost Management: Provides built-in features for tracking costs and setting budgets per user or API key.
• Enterprise Edition: An enterprise version offers additional features like SSO integration, audit logs, and role-based access control, which are often necessary for regulated environments.

4. Cloudflare AI Gateway

Cloudflare AI Gateway is a managed service that proxies LLM requests through Cloudflare's global edge network. While not a traditional on-premise solution, it can be used to manage traffic for self-hosted models.

• Best for: Teams looking for a managed gateway with global distribution, caching, and analytics that can proxy requests to both public and private, self-hosted LLM endpoints.

Key Features:

• Deployment Model: As a managed service, it does not offer a true air-gapped deployment. However, it can be configured to route requests to on-premise inference servers, providing a control plane that sits outside the private network.
• Edge Caching: Leverages Cloudflare's network to cache responses, reducing latency and cost for repeated queries.
• Analytics and Logging: Provides a dashboard for monitoring usage, costs, and performance across all providers from a single location.
• Limitations for Regulated Use: The primary drawback for strictly regulated industries is that prompts and metadata flow through Cloudflare's network, which may conflict with data residency and sovereignty rules.

Choosing the Right Gateway for Your Industry

The choice of an AI gateway in a regulated environment hinges on the specific compliance and security posture of the organization.

• For healthcare organizations subject to HIPAA, the ability to run in an air-gapped or VPC environment is critical to ensure Protected Health Information (PHI) is never exposed. A gateway must provide detailed audit logs and access controls to demonstrate compliance.
• In financial services, regulations require strict auditability, data protection, and transparent risk management. Gateways that integrate with existing identity and security systems are essential.
• Government agencies often operate under frameworks like the NIST AI Risk Management Framework and may require full air-gap capabilities for handling sensitive or classified information.

For organizations facing these stringent requirements, a solution like Bifrost offers the most complete package. Its combination of high performance, extensive security controls, and true air-gapped deployment flexibility provides a robust foundation for building compliant, secure, and scalable AI applications.

Teams evaluating on-premise AI gateways can request a Bifrost demo or review its capabilities in the open-source repository.