Systems | Development | Analytics | API | Testing

Scalable AI Economics: Achieving Secure, Hybrid Intelligence with Cloudera, AMD, and Dell Technologies

Enterprise interest in generative and agentic AI has accelerated dramatically over the past two years. Organizations across industries are exploring how AI agents, intelligent assistants, and automation can improve productivity, streamline operations, and unlock insights from growing volumes of enterprise data. Yet as enthusiasm grows, so do questions around cost, security, and operational complexity.

Web Application Testing: Tools, Types, and Best Practices

You deploy a web app. Users open it. Something breaks. It could be a button that doesn't respond on Safari. A form that submits twice on slow connections. A page that loads fine for 10 users but crashes for 500. These aren't rare edge cases. They're what happens when testing gets skipped, rushed, or treated as a final step before launch. It's not one activity. It's a system of checks that runs across the entire development lifecycle, from the first commit to post-deployment monitoring.

New Forrester report reveals a 403% ROI for Tricentis SAP quality assurance solutions

Modern SAP customers often face competing demands. While navigating the routine complexities of an SAP system, they must also prepare for faster releases and looming S/4HANA deadlines, juggling the day-to-day with long-term innovation. Intelligent quality assurance helps SAP users balance these priorities.

Designing error models in OpenAPI for agent-safe APIs | Swagger Studio

Poorly documented or inconsistent error models lead to brittle clients and unreliable automation. Whether you're building APIs for human developers or AI agents, proper error handling is crucial for automation and reliability. In this guided tutorial, SmartBear Solutions Engineer Rosemary Charnley demonstrates how to design robust error models in OpenAPI specifications using Swagger Studio.

The Breakdown | API calls and mobile apps

You used an API this morning. Probably before you even got out of bed. That weather app? It's your phone communicating with a server in the cloud — sending a request, getting data back, and displaying it on your screen in seconds. Location. Request format. Expected response. That's the anatomy of an API call. And it's happening constantly across nearly every app on your phone. Hugo Guerrero and Amanda Alcamo break it all down in Episode 2 of The API & AI Breakdown. No jargon. No fluff. Just clarity.

How ThoughtSpot Is Powering the Agentic Analytics Growth Across EMEA

The EMEA region is undergoing a massive transformation, driven by companies demanding instant, actionable insights embedded directly into their applications and workflows. This fundamental shift away from legacy BI has translated into record-breaking momentum for ThoughtSpot, positioning EMEA as our fastest-growing region globally. The Agentic Analytics revolution is here, and ThoughtSpot is delivering on the promise to make the world more fact-driven.

How AI Is Redefining Route Optimization to Enable Faster Deliveries?

When executives talk about improving logistics performance, the conversation often circles around the same three goals: speed, cost efficiency, and reliability. Yet the reality on the ground tells a different story. Traffic congestion, rising fuel costs, driver shortages, changing customer expectations, and unpredictable disruptions continue to make route planning one of the most complex operational challenges in logistics. Now add one more pressure point: customer expectations have fundamentally changed.

WSO2 AI Gateway: Prompt Management & Semantic Caching

Learn how to ensure consistent AI interactions and drastically reduce latency using the WSO2 AI Gateway. This step-by-step tutorial demonstrates how to standardize your LLM requests for quality and efficiency while cutting down on redundant API costs. We explore "Prompt Management" to enforce organizational guidelines using templates and decorators, and "Semantic Caching" to leverage vector embeddings—serving instant, cached responses for semantically similar queries to minimize expensive LLM calls.