New MCP Support Across the Entire Konnect Platform

If you’ve been following Kong, you know that Kong was the first in the API platform space to introduce an enterprise-grade AI Gateway for LLM workloads. Today, we’ve also introduced a new enterprise-grade MCP Gateway to ensure that you can roll out production-ready MCP deployments. But we are…
Make MCP Production-Ready: Introducing Kong’s Enterprise MCP Gateway

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…
From Chaos to Control: How Kong AI Gateway Streamlined My GenAI Application

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,…
The Observability Gap: Why API and AI Monitoring Must Converge Now

Disruptive businesses are understandably rushing to deploy AI-native applications alongside traditional API infrastructure. However, managing observability across both domains (API and AI) while keeping a tab on performance visibility and operational control remains a pressing challenge. AI…
AI Guardrails: Ensure Safe, Responsible, Cost-Effective AI Integration

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…
Announcing the Kong Agentic AI Hackathon

Calling all builders, tinkerers, and API innovators. The Kong Hackathon is back for API Summit 2025 ! This year, we’re challenging developers worldwide to create projects that don’t just react, they think , adapt , and act . The theme? Agentic AI : solutions that take initiative, make decisions,…
Securing Enterprise AI: OWASP Top 10 LLM Vulnerabilities Guide

Organizations are going all-in on large language models (LLMs), with research finding 72% anticipate increased LLM spending in the coming year (and about 40% are already investing more than $250,000 USD per year). As enterprises rapidly adopt LLMs to transform customer experiences, automate…
How to Build a Multi-LLM AI Agent with Kong AI Gateway and LangGraph

In the last two parts of this series, we discussed How to Strengthen a ReAct AI Agent with Kong AI Gateway and How to Build a Single-LLM AI Agent with Kong AI Gateway and LangGraph . In this third and final part, we're going to evolve the AI Agent with multiple LLMs and Semantic…
How to Build a Single LLM AI Agent with Kong AI Gateway and LangGraph

In my previous post, we discussed how we can implement a basic AI Agent with Kong AI Gateway. In part two of this series, we're going to review LangGraph fundamentals, rewrite the AI Agent and explore how Kong AI Gateway can be used to protect an LLM infrastructure as well as external functions.…
How to Strengthen a ReAct AI Agent with Kong AI Gateway

This is part one of a series exploring how Kong AI Gateway can be used in an AI Agent development with LangGraph. The series comprises three parts: Basic ReAct AI Agent with Kong AI Gateway Single LLM ReAct AI Agent with Kong AI Gateway and LangGraph Multi-LLM ReAct AI Agent and LangGraph Server…
Kong AI Gateway 3.11: Reduce Token Spend, Unlock Multimodal Innovation

Today, I'm excited to announce one of our largest Kong AI Gateway releases (3.11), which ships with several new features critical in building modern and reliable AI agents in production. We strongly recommend updating to this version to get access to the latest and greatest that AI infrastructure…
Build Your Own Internal RAG Agent with Kong AI Gateway

What Is RAG, and Why Should You Use It? RAG (Retrieval-Augmented Generation) is not a new concept in AI, and unsurprisingly, when talking to companies, everyone seems to have their own interpretation of how to implement it. So, let’s start with a refresher. RAG (short for Retrieval-Augmented Gener…