Systems | Development | Analytics | API | Testing

Test the Untestable With Perfecto AI: GUI Cards

Discover how Perfecto AI streamlines the testing of complex GUI cards and collapsible menus, a common challenge in modern application design. This demonstration reveals how a single, natural language prompt can execute sophisticated tests across multiple platforms, saving significant time and effort. What you will witness.

Test the Untestable With Perfecto AI: Nested Tables

Discover how Perfecto AI simplifies automated testing for complex and nested tables, a common challenge in data-intensive applications. This short demo showcases how a single, natural language prompt can execute sophisticated data validation across multiple platforms, simplifying a traditionally difficult and time-consuming process. What you will see in this demonstration.

Test the Untestable With Perfecto AI: Complex Diagrams

Watch how Perfecto AI validates complex diagrams, verifying elements such as object positioning, color accuracy, and labeling correctness. With agentic AI, these traditionally difficult areas for test automation are simplified using natural language prompts. Get ready to explore.

Introducing the MCP Server - Testing Reimagined in Katalon Studio

Hey everyone, Launch days are always exciting, and today, I couldn’t be happier to share something we’ve been working hard on: the MCP Server in Katalon Studio. This isn’t just another update. It’s a milestone for StudioAssist and for all of you who are looking to move faster with AI. With this release, we evolved StudioAssist from simply answering your questions to becoming your Agentic AI assistant. That means it doesn’t just tell you what to do.

Ep 42 | AI as a New Class of Risk with Ojas Rege

AI as a New Class of Risk with Ojas Rege. AI is changing the way businesses operate. But without trust, governance, and accountability, progress stalls. Ojas Rege, SVP & GM, Privacy & Data Governance at OneTrust joins The AI Forecast to explore how organizations can balance innovation with responsibility. He and host Paul Muller unpack why AI represents a “new class of risk,” what it means to design privacy and governance into systems from the very beginning, and how curiosity and context fuel better decision-making with data.

Inside AI Engineer Paris 2025 Part 1 - 5 Highlights That Shaped the Stage

At Koyeb, we run a serverless platform for deploying production-grade applications on high-performance infrastructure—GPUs, CPUs, and accelerators. You push code or containers; we handle everything from build to global deployment, running workloads in secure, lightweight virtual machines on bare-metal servers around the world.

Monetizing Content Through API for LLM Training

To monetize digital content, we have used means like ad networks, affiliate links, and paywalls. However, with the fast and widespread adoption of AI, demand for high-quality data has increased. To make sure Large Language Models (LLMs) models deliver value and accurate results, a wide spectrum of content is often scraped and trained on without permission or compensation. This includes blogs, product and technical docs, forums, and research papers.

How to Best Plan Usage-Based Pricing For AI Agents

The rise of AI agents has reshaped software economics; businesses have been increasingly adopting them for efficiency, scale, and delivering values faster. However, pricing them has remained a hard problem. By the established norms, you would tie cost to headcount or access, but that doesn’t fit; traditional methods misalign with how agents deliver value. And newer approaches often create more confusion than clarity.