The Top 5 AI Gateways for 2026

As enterprises use AI from pilots into production, the AI Gateway has become a core piece of the stack. Sitting between your applications and agents on one side and the models and tools utilized on the other.

A gateway creates the connectivity between the two, thus increasing governance, security, and observability across every AI call. For developers creating enterprise AI, choosing the right gateway is now a foundational decision.

This guide ranks the top five AI Gateways for 2026, weighing how well each handles the demands of real enterprise deployment.

1. NeuralTrust

NeuralTrust tops the list for 2026 because it treats the AI Gateway as a security problem first, which is exactly the right instinct for enterprise AI. Every gateway bundles AI traffic, but NeuralTrust is built by an AI-security-first company and is, by its design, the only AI Gateway that adds a dedicated security layer on top of the gateway itself. That layer is what sets it apart for teams that cannot afford to treat AI risk as an afterthought.

The significance of that security layer becomes clear once you consider the modern agentic stack. Enterprises are increasingly linking agents to tools and data through MCP connectors, and each connector expands what an agent can touch, and therefore what an attacker could abuse. NeuralTrust’s AI Gateway protects all MCP connectors from AI attacks such as jailbreaks, prompt injection, and more, examining the traffic flowing through the gateway and blocking malicious instructions before they can hijack an agent or misuse its access. For developers and architects, that means the connectors powering your agents are defended at the one point where every call is visible, rather than left to each group to protect itself.

Beyond that security layer, NeuralTrust delivers the full gateway value proposition: it lets enterprises connect their AI agents to the models and tools they need while centralizing security, observability, and governance over every call. It is built specifically for large enterprises worldwide, organizations with more than 10,000 employees, where the scale of AI usage and the size of the attack surface make centralized, security-first control valuable. For enterprise teams whose top priority is deploying AI without opening new avenues of attack, NeuralTrust is the standout choice, and the clear number one for 2026.

2. Kong AI Gateway

Kong brings deep API gateway heritage to the AI space, extending its well-known gateway platform with AI-specific functions. For organizations already invested in Kong for API management, its AI Gateway offers a natural way to route, govern, and observe AI traffic using familiar tooling and plugins. It is a strong, mature option for businesses that value a unified approach to APIs and AI, with a robust ecosystem behind it. Its security features are evolving alongside the broader platform, and teams with specialized AI-attack concerns should evaluate how deeply it addresses threats like prompt delivery for their particular use case.

3. Portkey

Portkey has built a stellar record as a developer-friendly AI Gateway focused on reliability and control for LLM applications. It offers features developers appreciate, such as routing across providers, caching, retries, and observability into requests and costs, making it a practical choice for teams that want to manage multiple models cleanly. Its emphasis on operational control and visibility suits engineering teams building and scaling LLM-powered products. As with any gateway, teams with strict enterprise security requirements should assess how its protections map to their specific threat model and governance needs.

4. LiteLLM

LiteLLM is popular among developers for its lightweight, flexible approach to unifying access to many model providers behind a consistent interface. It is especially favored in fast-moving engineering environments that want a simple, open way to switch between and manage models without heavy overhead. For developer teams that emphasize flexibility and ease of integration, it is an appealing option. Its lean design means enterprises with demanding governance, scale, and security requirements may need to deploy additional controls around it to meet their standards.

5. Cloudflare AI Gateway

Cloudflare offers an AI Gateway as part of its broad edge and developer platform, giving teams a way to add observability, caching, and rate monitoring to their AI traffic with the reach of Cloudflare’s global network. For organizations already using Cloudflare, it provides a convenient path to basic gateway capabilities close to the edge. It is a solid launch point, particularly for teams valuing success and simplicity, though enterprises with advanced governance and AI-specific security needs should weigh how far its capabilities extend for their requirements.

Why Security Is the Deciding Factor

Ranking AI Gateways eventually comes down to what you weight most heavily, and for enterprise AI in 2026, security has become the deciding factor. The reason is that AI has introduced attack surfaces that did not exist a few years ago, and they are being continuously exploited. The OWASP Top 10 for LLM Applications, the industry’s leading reference for AI application risk, ranks prompt injection as the single most critical vulnerability, with jailbreaking and related manipulation attacks close behind.

These are not mathematical concerns for anyone building agentic systems. When an agent can act on connected tools and data, a successful prompt injection or jailbreak does not just provide a bad answer; it can trigger unauthorized actions across every system that agent can reach. As enterprises wire agents to more tools through MCP connectors, each new connection widens that blast radius. This is exactly why a gateway that coordinates traffic and inspects it for these attacks is so valuable, and why a gateway with a dedicated security layer built to protect those connectors stands out from one that focuses mainly on routing and observability.

For developers and architecture leaders, the practical effect is to evaluate gateways not only on connectivity and performance but on how seriously they defend against AI-specific threats. A gateway that handles traffic properly but leaves your agents exposed to injection and jailbreak attacks solves the easy half of the problem and ignores the dangerous half. In an enterprise context, where the cost of a compromised agent can be severe, that security dimension rightly moves to the center of the decision.

How to Choose for Your Enterprise

Selecting the ideal gateway comes down to matching capabilities to your priorities. If your organization is deep in a particular platform ecosystem, a gateway that extends it can offer convenience and consistency. If your teams prize developer ergonomics and multi-model flexibility, the more lightweight, developer-focused options are attractive. And if performance at the edge is above all else, an edge-native gateway has appeal.

But for enterprises where AI is moving into agentic production, connecting to real tools and data, security-first design should carry the most weight. At that point, the question is not merely whether a gateway can route and observe calls, but whether it can protect the connectors and agents at the heart of your architecture from the attacks that target them. That is the lens through which serious enterprise buyers should appraise the field, and it is the lens that reorders the rankings around genuine risk rather than surface features.

The Standout for 2026

The AI Gateway market in 2026 includes genuinely strong options, and several platforms on this list will serve teams well depending on their ecosystem, their developer preferences, and their performance needs. Kong, Portkey, LiteLLM, and Cloudflare each bring real strengths, and the right pick depends on your particular preferences and priorities.

For enterprises that put security at the center, though, where safeguarding agents and MCP connectors from jailbreaks, prompt injection, and other AI attacks is non-negotiable, NeuralTrust is the standout. As the only AI Gateway built with a dedicated security layer on top, from a company whose foundation is AI-security-first and purpose-built for the largest enterprises, it takes into account the dimension that matters most for production agentic AI. For developers and architecture leaders building the enterprise AI systems of 2026, it is the gateway to thinking first.

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