We are thrilled to announce the arrival of Tricentis Testim Copilot, the first of many Tricentis Copilot solutions. Tricentis Copilot solutions are a collection of advanced generative AI capabilities available as add-ons across our products that help customers boost their efficiency throughout the entire testing lifecycle. With Testim Copilot, we’ve added new advanced generative AI capabilities to Testim, an already AI-driven test automation platform.

Kong Mesh 2.7 is here! And with it come a slew of new features to make our simple and powerful enterprise service mesh even easier to use and more powerful for your particular needs. In this blog post, we'll cover the new features and show how Kong Mesh 2.7 can deliver a superior service mesh experience for your organization.

We're excited to introduce WSO2 API Platform for Kubernetes (WSO2 APK) 1.1, a key update to our Kubernetes-native API management solution. This release leverages the strengths of Kubernetes to offer high-performance and cloud-scale API management, ensuring automation, reliability, and improved developer experiences. Traditional API management solutions aren't built for Kubernetes environments, leading to issues with performance, scalability, and manual configuration.

We’re delighted to announce the release of WSO2 API Manager 4.3, a significant upgrade that enhances your API ecosystem's performance, security, and scalability. WSO2 API Manager, an industry-leading open source API management solution, offers a unified platform for creating, publishing, and overseeing APIs, enabling organizations to securely expose their services with both internal and external stakeholders.

Kong Insomnia 9.0 is now generally available for download. It ships with many new features and improvements — over one hundred improvements in total! This new version of Kong Insomnia also makes it much easier to migrate from other products with a more reliable “import” experience, while improving the speed of using the product and making it more customizable. Let’s dive into all the notable features.

Building top-tier enterprise-grade intelligence using LLMs has traditionally been prohibitively expensive and resource-hungry, and often costs tens to hundreds of millions of dollars. As researchers, we have grappled with the constraints of efficiently training and inferencing LLMs for years.