Systems | Development | Analytics | API | Testing

Embed Quality to Ensure Regulatory Compliance in FinTech Solutions

This article originally appeared on Software Testing News. We’re sharing it here for our audience who may have missed it. An overlooked API can expose customer data, trigger multi-million-dollar fines, and sink a FinTech product launch. And now, the FinTech industry is at a crossroads, driven by innovation yet bounded by intensifying regulatory demands.

Why API-First Matters in an AI-Driven World

APIs have long been the backbone of modern software systems, architectures, and businesses. They now dominate the web, accounting for 71% of all internet traffic. Generative AI is accelerating this trend especially as we pivot our interaction with common web-based capabilities, like “search” in favour of AI-enriched variants. More AI leads to more APIs, and with that, APIs act as an important mechanism to move data into and out of AI applications, AI agents, and Large Language Models (LLMs).

Build Your Own Internal RAG Agent with Kong AI Gateway

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 Generation) is a technique that injects relevant data from an external knowledge source directly into a prompt before sending it to a Large Language Model (LLM). “But wait, my model is already fine-tuned on my domain-specific data.

Kong Gateway Enterprise 3.11 Makes APIs & Event Streams More Powerful

We’re excited to bring you Kong Gateway Enterprise 3.11 with compelling new features to make your APIs and event streams even more powerful, including: We’ll also touch on what’s new with Konnect networking and Active Tracing. There’s a lot to unpack, so keep on reading for the full story!

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 has to offer.

TDC S6E12 16x9 v02

Step inside the world of data innovation as Cindi Howson talks with Josh Cunningham, Group Head of Data and AI Culture at @lloydsbankonline. They'll explore how this distinguished institution is driving forward with cutting-edge AI. Discover how Lloyds is rapidly expanding its data and AI graduate scheme and pursuing an ambitious quest to become the "most data literate bank". Hear how innovative initiatives like the "Data and AI Summer School" and a physical "Data Escape Room" are used to teach "learning by stealth", propelling their business forward on data and AI.

Your Data Stack Needs An Upgrade - Here's Why

What if prepping, integrating, and modeling your data was as simple as chatting with an AI agent? No complex configurations. No steep learning curves. Just fast, intelligent results powered by natural language and agentic AI. In Episode 3 of the Round Table Series, we explore why an Agentic Data Management Platform is the next generation of data technology. It is smarter, faster, and fully autonomous.

It's time to start prioritizing every side of API discovery

Join us for a deep dive into API discovery – and why it’s time to treat it like a first-class priority. In this session, we’ll explore what we mean by the “two sides of API discovery” and why unifying both sides with a comprehensive solution is critical to driving API adoption and reuse, strengthening your organization’s security posture, and mitigating the financial and developer productivity-related costs associated with API sprawl.

Beyond console.log: Smarter Debugging with Modern JavaScript Tooling

Ask any JavaScript developer their most used debugging tool and chances are the answer will be console.log. It’s immediate, low friction, and available in every browser. For development, it’s fantastic. But for production and complex applications, if you rely on console.log alone, cracks begin to show. It lacks context, doesn’t persist, and makes reproducing or analyzing user-reported issues a challenge. In this article, we’ll look at smarter, scalable debugging strategies.