Systems | Development | Analytics | API | Testing

Turn quality into a strategic advantage—accelerate outcomes with Sauce intelligence.

Your data warehouse holds untapped potential for generative AI (GenAI), but there's a problem: most systems lack the right connection to make this work seamlessly. Enter the Data AI Gateway - a middleware solution designed to bridge the gap between massive datasets and AI systems. This tool not only streamlines integration but also tackles key challenges like data security, real-time access, and cost management.

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.

The Model Context Protocol (MCP) is quickly becoming a foundational layer for AI systems. It enables large language models and AI agents to interact with external tools and data sources over standardized JSON-RPC interfaces. By doing so, MCP transforms how intelligent applications consume APIs. Reading local files, controlling IoT devices, orchestrating backend workflows—MCP servers act as structured gateways between AI and your business logic.

Picture the scene. You're sitting in yet another budget meeting, and someone inevitably pipes up with the golden question: "Why are we paying for seven different tools when we could just use one?" Everyone applauds. Confetti bursts from the ceiling. There’s a cake for some reason. That’s the siren song of vendor consolidation. It's everywhere these days, and honestly? It makes sense. Finance loves it because it’s cost savings that can be easily represented as a budget line item.

With the EU AI Act now in force, compliance is no longer about aspirational ethics or last-minute checklists, it’s about operationalizing quality assurance at every stage of your AI lifecycle.

South Africa’s Joint Standard on Cybersecurity & Cyber Resilience (JS2) is reshaping the regulatory landscape. Financial institutions must now rethink how they manage sensitive data. For data compliance leaders, this marks a critical shift where failing to adapt could bring serious consequences. This blog will examine what JS2 means for your organization’s data compliance efforts. Then, discover how Perforce solutions can help you in building a resilient data compliance program.

Staging environments are often looked at as the testing ground ahead of the “real” production environment. The idea is simple – build a duplicate of your production environment, run your tests, and ship with confidence. But the reality of using staging in the real world as part of a holistic API testing strategy is rarely that clean. No matter how meticulously you mirror production services, staging always falls a little short.

Imagine a world where every backend, legacy system, cloud database, and app is instantly connected—no manual coding, no ongoing maintenance headaches. As businesses rush to unlock value from data, API gateways are becoming critical infrastructure. The most advanced platforms now go beyond traditional API management—bringing AI, automation, and security into the integration layer.

So you’re diving into the world of API documentation tools? Trust me, I have been there before. When I first started working with APIs, I thought documentation was just something you threw together at the last time. And I was completely wrong! The impact of AI on code commenting and software documentation is becoming more evident every day. Good API documentation can literally make or break your projects success.