Systems | Development | Analytics | API | Testing

ThoughtSpot June Release: Customize Your Agent

Check out what’s new in ThoughtSpot’s latest release! SpotterModel gets smarter: Build complex data models with AI formula suggestions and instant version rollbacks if you make a mistake. No stress, no lost work. Spotter Instructions: Fully customize Spotter’s persona, formatting rules, and strict guardrails. It says exactly what you want it to say—and nothing it shouldn't. Ad Hoc Analysis: Drop local files directly into Spotter for instant answers, or blend them safely with your governed enterprise data.

Stop testing everything: How Tricentis SeaLights tells you exactly what to test

Most teams don't know which parts of their code have actually been tested, and which haven't. That gap is where defects escape. Tricentis SeaLights is a quality intelligence platform that gives engineering and QA teams real-time visibility into test coverage. It maps every code change to the tests that cover it, surfaces exactly what's tested and what isn't, and recommends which tests to run and which to skip across unit, regression, integration, manual, and end-to-end tests.

Introducing AI Test Prioritization and New AI Capabilities for Smarter Testing in Jira

With the release of Xray Cloud 15.0.0, Xray expands its latest AI capabilities with the introduction of AI Test Prioritization, joining two recently released features: Xray's Rovo Test Plan Summarizer and AI-generated Manual Scripts for Test Case Designer, introduced in Xray Cloud 14.0.0. Testing is rarely just about executing test cases. Teams need to understand where risk exists, how testing is progressing, and whether a release is ready to move forward.

Safeguarding Multi-Brand E-Commerce: Architectural Quality Engineering for Enterprise Scale

When you operate a digital commerce ecosystem across multiple international borders, processing thousands of concurrent checkout events for over 70 global brands, the standard concept of "QA" completely breaks down. Most corporate discussions treat software validation as a simple pre-release checklist, a final mechanical hurdle before a deployment goes live.

How AI Inference Is Reshaping Enterprise Infrastructure

Data center teams are skilled at solving familiar problems such as storage outages, missed forecasts, and late refresh cycles. These are known quantities. Teams have playbooks for them. But 2026 has brought a different kind of pressure. After years of enterprise AI investment concentrated almost entirely on model training, the industry has crossed a threshold: the workload that now defines AI infrastructure isn’t building models. It’s running them. Continuously. At scale. Every day.

Introducing the Skills Marketplace: AI analyses on your data, with expert judgment built in

Every team we talk to has a running list of questions they wish they could get fast, reliable answers to. What changed in our performance last month and why. Which clients are showing the early signs of churn. Which channels are actually pulling weight and which ones are quietly burning budget. The pull toward AI for this kind of work is obvious. The answers should be a question away.

Why Your D365 Test Automation Strategy Needs a Rethink Before May 2027

If you’re running Microsoft Dynamics 365 and relying on RSAT (Regression Suite Automation Tool) to keep your test automation ticking, there’s a deadline you cannot afford to ignore: RSAT support ends on 15 May 2027. That’s not far away, and the decisions you make now will shape how painlessly your QA practice survives the transition. So let’s talk about what comes next and why the answer is more interesting than you might expect.