Scaling LLM and agentic AI adoption from pilot programs to enterprise-wide deployments is a massive logistical rollout. As AI and agentic usage grow, so does a nagging question for leadership: Are agents using the right tools to get the job done? While raw infrastructure metrics might tell you if a…
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When enterprises started experimenting with LLMs, the governance challenge — while still difficult — was relatively contained once you had an AI Gateway for LLM traffic. You had a request going to a model, a response coming back, and a gateway in between to enforce policy. With the right solutions,…
[](/blog/product-releases/kong-agent-gateway)
Every enterprise moving AI into production is about to face a familiar problem in an unfamiliar form: the cost explosion, but for LLMs. This is very similar to what happened with cloud. In the early days of cloud, teams spun up infrastructure with no visibility into who was consuming what. Finance…
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AI APIs don't get enough credit for how much weight they're actually carrying. These AI APIs aren't merely technical connectors. They're, in fact, cost drivers and potential revenue engines. And when something goes sideways, they're ground zero. In production, they behave nothing like the…
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In the burgeoning intelligence economy, AI tokens are a metered utility, but enterprise profitability now hinges on a critical distinction: output tokens can cost up to 10x more than inputs, creating a new, invisible risk for cost overruns, particularly with Agentic AI. Learn how Kong AI Gateway…
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While every organization races to deploy AI agents faster, finance departments are watching something alarming unfold—and it will play a large part in determining who survives the agentic era. The numbers are stark: 84% of companies report more than 6% gross margin erosion from AI costs. Within…
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Have you ever asked an AI assistant to generate code for a framework it doesn't quite understand? Maybe it produces something that looks right, but the syntax is slightly off, or it uses deprecated patterns. The AI is working hard, but it lacks the specific context it needs to truly help you. The…
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The agentic era is here, and it's exposing a critical gap in enterprise infrastructure. AI agents are no longer experimental. As many as 9 out of 10 enterprise organizations are actively adopting AI agents. Agents are making autonomous decisions, orchestrating complex workflows, and interacting…
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Kong AI Gateway 3.13 moves enterprises from AI experimentation to shipping production-grade agents by unlocking new capabilities focused on agentic security, developer productivity, and resilience, including MCP tool-level access control, expanded provider support, and smarter load balancing. We…
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The integration of next-generation AI workloads — from large language models (LLMs) to speech-to-text and text-to-speech — demands a powerful, secure, and scalable infrastructure. This is especially true for building advanced AI voice agents, which rely on seamless, natural, and highly efficient…
[](/blog/engineering/ai-voice-agents-kong-ai-gateway-cerebras)Everyone's telling you to innovate faster with AI. Move quicker. Ship more features. Deploy more agents. But before we sprint headlong into the AI revolution, we need to have a proper dollars-and-cents conversation that most companies are avoiding. Disclaimer: Statistics cited in this post were…
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Today, we're open-sourcing Volcano SDK, a TypeScript SDK for building AI agents that combines LLM reasoning with real-world actions through MCP tools. Why Volcano SDK? One reason: because 9 lines of code are faster to write and easier to manage than 100+ . Without Volcano SDK? You'd need 100+ lines…
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The Model Context Protocol (MCP) represents a transformative shift in how AI agents connect to data and tools, but the path to production-readiness and real-world AI value is still fraught with challenges. As organizations rush to adopt MCP and build agentic workflows, they're encountering four…
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Disclaimer: All of the opinions stated in this blog are my own and do not represent official Gartner opinions on the API Management and Integration markets or the Magic Quadrant report itself. The 2025 Gartner Magic Quadrant for API Management report was a great one for us here at Kong. We continue…
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In this post, Kong Champion Sachin Ghumbre shares his journey of transforming a complex GenAI application from a state of operational challenges to streamlined control. Discover how Kong AI Gateway provided the enterprise-grade governance needed to secure, optimize, and scale his GenAI solution,…
[](/blog/engineering/how-kong-ai-gateway-streamlined-my-genai-application)
As enterprises increasingly embed AI and Large Language Models (LLMs) into their digital experiences, enforcing robust AI guardrails becomes paramount to safeguard users, protect data, manage operational costs, and comply with regulatory and ethical standards. Think of AI guardrails as essential…
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