Systems | Development | Analytics | API | Testing

Accelerating GenAI Adoption in Financial Services

"Watch the full Cloudera webinar replay: Accelerating the Adoption of Generative AI in Financial Services. This comprehensive session outlines a step-by-step framework for moving from pilot projects to enterprise-wide AI adoption, covering everything from data strategy to governance and use case prioritization. This is your essential guide to a faster, more secure GenAI rollout.

Top Sandbox Platforms for AI Code Execution in 2025

In 2025, as AI models increasingly generate, refactor, and deploy code on their own, developers face a new challenge: how to safely run code they didn’t write. Sandboxes have become the backbone of this new workflow because they are lightweight, secure environments that let teams test, validate, and monitor code without risking production systems.

From Data to Decisions in Seconds: Meet Spotter's New Research Mode

Unlock deeper business insights with Spotter’s new research mode. This powerful agent intelligently analyzes questions to uncover key findings, investigates key metrics, and then delivers them as a structured decision report. Tackle your biggest business challenges with just a simple question. Go from insight to strategy in seconds. See research mode in action!

End Data Disparity | A Deep Dive Into The Realities Of ESG Financial Initiatives

In this interview in the new "End Data Disparity" video series, host Ryan Green chats with Elena Philipova, Director of Sustainable Finance & Investment and Data & Analytics at LSEG (London Stock Exchange Group). She talks about her experience leading ESG (Environmental, Social, and Governance) initiatives at leading financial companies and the significant changes she has seen in the area of sustainable finance.

The AI Blueprint for the Next Decade | BUILD 2025 Luminary Conversation

AI has already fundamentally changed how we interact with data on a daily basis, and it’s going to keep changing. As we embrace agentic and conversational AI tools, there remain foundational questions to answer about how and where we use this technology, and how we iterate and innovate with it for the future. Join Snowflake CEO Sridhar Ramaswamy for a fireside chat with two of the most influential figures in artificial intelligence: Andrew Ng, Executive Chairman of LandingAI and founder of DeepLearning.AI, and Swami Sivasubramanian, VP of Agentic AI at Amazon Web Services.

DreamFactory Data Integration Logging Best Practices

Data integration logging is the process of recording events and activities during data movement across systems, ensuring accuracy, troubleshooting, and regulatory compliance. In complex environments like those of Netflix and Airbnb, logging is critical for system reliability and performance. However, challenges such as managing large log volumes, inconsistent formats, and compliance requirements make effective logging difficult.

How To Use Software Testing Metrics To Drive Better Qa Decisions

Why do some QA teams consistently deliver reliable and high-quality software, while others toil to identify bugs and experience unstable releases? The real difference often is related to how easily the team is able to use software testing metrics to make measurable decisions. Often, the testing process turns out to be a routine checklist activity – run the tests, publish the results, and move on. However, without useful test metrics, the QA teams simply keep guessing.

Introducing the Katalon Support Assistant: Smart Support, Faster Answers

Getting the right answer to a technical question, right when you need it, can be the difference between a minor speedbump and a major roadblock. We all know the feeling of being stuck on a specific error or needing a quick "how-to" guide to keep a project moving. That's why we’re excited to announce that the new 24/7 Katalon Support Assistant is now live in production! It's an AI-powered technical support agent and the fastest way to get the help you need, anytime.

Building a Business Case for Test Automation in Insurance industry

Insurance companies face unique challenges in delivering reliable software quickly. Policy updates, claims processing, and regulatory compliance all demand precision and speed. Manual testing alone can create delays, introduce errors, and increase operational risk. That's where test automation for insurance industry comes in. Repetitive regression tests that previously take up so much time can easily be automated.