SiliconANGLE Media runs this [_annual awards program_](https://www.thecube.net/awards)_annual awards program_ to recognize companies, technologies, and people moving the needle in B2B tech. Winners go through a review process by industry analysts and experts.

Kong was recognized as the 2026 AI Innovator of the Year for its role in building the connectivity layer for the AI era, unifying APIs, AI models, events, and agentic systems through a single control plane. As we enter [_the age of AI connectivity_](https://konghq.com/blog/news/the-age-of-ai-connectivity)_the age of AI connectivity_, organizations must move from AI experimentation to production without losing control over data access, model usage, and costs. 

To achieve this, the Kong platform provides granular control over AI traffic. This ensures that every interaction with a large language model (LLM) is authenticated, governed by policy, and audited for compliance — solving the critical challenge of "shadow AI" in enterprise environments.

Building [_an agentic AI developer platform_](https://konghq.com/blog/enterprise/agentic-ai-developer-platform)_an agentic AI developer platform_ with Kong enables secure, observable, and governed AI at scale, turning fragmented infrastructure into a coherent, interoperable foundation for intelligent applications.

Our approach to the AI connectivity layer is built on some key pillars:

1. - **Model-agnostic routing**: Seamlessly switch between models (like GPT-4, Claude, or Llama) without rewriting application code, addressing the need for flexibility in multi-cloud AI strategies.
2. - **Semantic intelligence**: Implement semantic caching and prompt guardrails to lower inference costs and secure data before it ever leaves your perimeter.
3. - **Unified observability**: Gain deep visibility into token usage, latency, and error rates across all your AI services from a single dashboard.

An award like this is meaningful because it's validation that what we're building is actually solving real problems at scale — not just chasing hype. Check out our library of [_customer stories_](https://konghq.com/customer-stories)_customer stories_ to see just a sampling of the real problems we've solved in orgs like yours.

As SiliconANGLE's John Furrier put it, this year's winners are the ones "looking beyond hype and focusing on building platforms and products that customers rely on." High praise! But building the foundations that builders and businesses rely on has and will always be a part of Kong's mission.

Kong operates at the connectivity layer between your applications, services, APIs, events, and AI models — running consistently across hybrid and multi-cloud environments. 

Kong functions as a unified AI and API platform, combining API management, AI traffic governance, identity integration, observability, and API monetization in one place, so you're not duct-taping a dozen tools together or getting locked into a single vendor. This unification allows teams to apply the same rigorous security and performance standards to their AI agents as they do to their traditional microservices.

As AI moves from a cool experiment to core enterprise infrastructure, that AI connectivity layer matters more than ever. And we're excited to keep building it.

Want to learn more about how Kong approaches AI connectivity? Check out[ ](https://konghq.com/ai-connectivity) [_konghq.com/ai-connectivity_](http://konghq.com/ai-connectivity)_konghq.com/ai-connectivity_. Or [_get a demo_](https://konghq.com/contact-sales)_get a demo_ today to see what Kong can do for you.

**What is an AI gateway?**

An AI gateway is a specialized infrastructure layer that manages, secures, and observes traffic between your applications and AI models (such as LLMs). Unlike a standard gateway, it includes specific features for AI, such as prompt engineering support, semantic caching to reduce costs, and model-agnostic routing to prevent vendor lock-in.

**How does Kong govern AI model API traffic at scale?**

Kong governs AI traffic by acting as a centralized control plane. It enforces policies such as rate limiting based on token usage, role-based access control (RBAC) for specific models, and data redaction to prevent sensitive information (PII) from being sent to public LLM providers.

**Why is the "AI Connectivity Layer" important for enterprises?**

As organizations adopt multiple AI models across different clouds, infrastructure becomes fragmented. The AI Connectivity Layer unifies these disparate elements, ensuring that security, identity, and observability are consistent regardless of which model or cloud provider is being used. This allows enterprises to move from experimentation to production securely.

**Can Kong operate in a multi-cloud AI environment?**

Yes. Kong is designed for hybrid and multi-cloud environments. It allows you to run your AI gateway close to your applications or models, whether they are on-premise, in AWS, Azure, or Google Cloud, providing a unified management experience across all infrastructure.