Top 5 Open Source AI Gateway Platforms for In-VPC Teams

Regulated teams increasingly need to run large language model traffic without any of it leaving their infrastructure. An open source AI gateway solves that by giving you a single control plane you can host yourself, audit line by line, and deploy where your data already lives. Bifrost, the open-source AI gateway built in Go by Maxim AI, was designed for exactly this: it routes 1000+ models through one OpenAI-compatible API while staying entirely inside your private cloud. Below we rank the top five platforms for in-VPC deployments and explain what separates them.

What Is an In-VPC AI Gateway?

An in-VPC AI gateway is a self-hosted proxy that routes and governs LLM traffic entirely inside your own virtual private cloud, with no calls leaving your network perimeter. Instead of relying on a vendor-managed endpoint, you deploy the gateway on your own compute, inside your own subnets, behind your own security groups. Provider API keys, prompts, and completions stay within a boundary you control. For a deeper look at how the routing layer works, see the Bifrost documentation overview.

Why Teams Keep AI Traffic In-VPC

Keeping AI traffic in-VPC comes down to four pressures that a public endpoint cannot fully address. The first is data residency: prompts often carry customer records, source code, or protected health information, and sending them across a public boundary can violate contractual or jurisdictional rules. The second is avoiding third-party data sharing, so no external processor ever sees raw inputs. The third is compliance, where frameworks such as SOC 2 from the AICPA, the HIPAA Security Rule from HHS, and GDPR all reward tight control over where regulated data flows. The NIST AI Risk Management Framework similarly treats data governance and traceability as core controls for trustworthy AI. The fourth is latency, since a gateway that sits next to your applications shaves round trips that a distant managed service adds. For how these map to enterprise controls, see the Bifrost enterprise page.

What to Look for in an Open Source AI Gateway for In-VPC Deployment

Not every gateway that calls itself open source is built for a locked-down network. Use these criteria to shortlist candidates, and cross-check them against a structured buyer's guide before you commit.

• Genuinely self-hostable and open source: source you can read, fork, and run without a hosted control plane.
• VPC, air-gapped, and on-prem support: the gateway should run with no public network egress, including in fully disconnected environments.
• Kubernetes and clustering: native container deployment plus high-availability clustering for production traffic.
• Data access control and audit logs: fine-grained access rules and immutable trails that map to compliance evidence.
• RBAC and SSO/OIDC: role-based permissions and identity federation with providers like Okta and Entra.
• Broad model coverage with no forced egress: access to many providers through one API, as in the Bifrost supported providers list, without routing through a vendor cloud.

1. Bifrost

Bifrost is the fastest and most complete open source AI gateway for teams that keep traffic in-VPC. Built in Go by Maxim AI, it adds only about 11 microseconds of overhead at 5,000 requests per second, and it acts as a drop-in replacement for the OpenAI API so existing code moves over without rewrites. It unifies routing, governance, and reliability in one binary you host yourself, which is why it sits at the top of this list.

• Access to 1000+ models through a single OpenAI-compatible API, with published benchmarks you can reproduce.
• Governance built in: virtual keys, budgets, and rate limits, detailed in the governance resources.
• Reliability features including automatic failover, weighted load balancing, and semantic caching.
• Observability through Prometheus, OpenTelemetry, and Datadog.

Best for: Bifrost is built for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability. It serves as a centralized AI gateway to route, govern, and secure all AI traffic across models and environments with ultra low latency. Bifrost unifies LLM gateway, MCP gateway, and Agents gateway capabilities into a single platform. Designed for regulated industries and strict enterprise requirements, it supports air-gapped deployments, VPC isolation, and on-prem infrastructure. It provides full control over data, access, and execution, along with robust security, policy enforcement, and governance capabilities.

2. LiteLLM

LiteLLM is a widely used open source proxy that normalizes calls across many model providers behind a single interface. Teams often reach for it early because it is lightweight and easy to stand up for basic routing. For deployments that need deeper governance, clustering, and audit depth, teams frequently compare it against alternatives, and you can read a side-by-side breakdown of the tradeoffs in this overview of LiteLLM alternatives.

• Unified API across multiple LLM providers.
• Self-hostable proxy suitable for smaller in-VPC setups.
• Community-driven ecosystem with broad provider coverage.

Best for: Teams that want a simple, self-hosted routing layer and are willing to add governance and reliability tooling separately.

3. Envoy AI Gateway

Envoy AI Gateway extends the Envoy proxy, a graduated CNCF project, with capabilities aimed at LLM traffic. It appeals most to organizations that already run Envoy or a service mesh and want to fold AI routing into that existing infrastructure. Because it is Kubernetes-native, it fits teams that treat the network layer as a first-class platform concern rather than an application add-on. Teams evaluating it often still want the deeper governance controls that a dedicated AI gateway provides.

• Built on the mature Envoy proxy foundation.
• Kubernetes-native and mesh-friendly.
• Suited to platform teams standardizing on cloud-native networking.

Best for: Organizations already invested in Envoy or service mesh tooling that want AI routing inside that stack.

4. Kong AI Gateway

Kong AI Gateway layers AI-specific routing and policy features on top of Kong's established API gateway. Teams that already operate Kong for general API management may find it convenient to extend the same plugin-based platform to LLM traffic. It can be self-hosted, which keeps it in scope for in-VPC evaluations. When comparing it to a purpose-built option, weigh how automatic fallbacks and model-level reliability are handled.

• Plugin-based architecture on top of Kong's API gateway.
• Self-hostable for private deployments.
• Familiar to teams already running Kong.

Best for: Teams standardized on Kong for API management that want to reuse that platform for AI traffic.

5. LangDB

LangDB is an AI gateway focused on routing across models with observability into request traffic. It can be run in self-hosted configurations, which keeps it relevant for teams that want to avoid a fully managed endpoint. As with any option on this list, confirm how it handles access control, audit trails, and clustering against your own requirements before adopting it. A structured buyer's guide can help you score it consistently.

• Routing across multiple model providers.
• Observability into AI request traffic.
• Self-hostable deployment options.

Best for: Teams that want combined routing and observability and are evaluating self-hosted gateways.

Deploying Bifrost Inside Your VPC

Bifrost was designed to run where your data already lives. You can deploy it through in-VPC deployments with no public network egress, including air-gapped and on-prem environments where nothing reaches the open internet. For production traffic, clustering provides high availability with automatic service discovery and zero-downtime deploys, and the Kubernetes deployment guide walks through running it on your own cluster, in line with the security model in the Kubernetes documentation.

On the control side, Bifrost provides data access control, RBAC, and SSO/OIDC with providers such as Okta and Entra, plus secure secrets management. Every action is captured in audit logs that produce immutable trails suitable for SOC 2, GDPR, HIPAA, and ISO 27001 evidence.

Frequently Asked Questions

What is the best open source AI gateway for self-hosting?

For teams that keep traffic in-VPC, Bifrost is our recommendation because it combines high performance, broad model coverage, and enterprise controls in a single self-hosted binary. It runs entirely inside your own infrastructure with no forced egress to a vendor cloud.

Can an AI gateway run air-gapped?

Yes. Bifrost supports fully air-gapped and on-prem deployments with no public network egress, so it can operate in disconnected environments where no request reaches the public internet.

How does an in-VPC AI gateway help with compliance?

Keeping AI traffic in-VPC means regulated data never crosses an external boundary, which simplifies data residency and third-party sharing obligations. Combined with data access control, RBAC, and immutable audit logs, it produces the traceability that frameworks like SOC 2, HIPAA, and GDPR expect.

Get Started with Bifrost

If you need an open source AI gateway that keeps every request inside your own network, Bifrost is ready for production in-VPC deployments today. Book a demo to see how our team can help you route, govern, and secure all AI traffic without giving up control of your data.