Systems | Development | Analytics | API | Testing

Another year has flown by at breakneck speed. In the data and analytics space, the past year has seen an AI gold rush where BI and analytics solutions raced to offer AI-powered insights to best meet end users’ rising expectations. But despite AI being named the most important trend of the next five years in an insightsoftware survey, it isn’t an exact science as organizations contend with AI projects that fail to launch and the risk of AI hallucinations.

With thousands of titles competing for a sliver of player attention, the margin for technical error in the modern gaming market has evaporated.

Every second a product sits out-of-stock on a shelf, revenue quietly drains away. Customers walk out empty-handed, and businesses lose customers as well as valuable insights into what’s actually happening on the floor. At Focal Systems, we have built Shelf AI, a system that continuously “sees” store shelves, detects stockouts, and guides teams to replenish in time—so products are on the shelf when customers need them.

AI is redefining how software is created and delivered. It’s transforming development speed, decision-making, and user expectations all while introducing new layers of complexity and risk. To keep pace, testing is evolving beyond automation into true AI-augmented testing, where intelligent systems help teams predict risk and defects, optimize coverage and efficiency, and deliver at the speed of AI-driven change. The industry has moved forward – now users need to catch up.

A practical guide to building traceability, governance, and evidence across the AI lifecycle.

Power to the people to make a point. According to Robert Gaskins 1, one of the original creators, that was the reasoning behind PowerPoint’s name, and alongside Google Slides and Keynote, it remains one of the World’s most powerful presentation software. Blog Contents show What is the problem with traditional presentation software? What you can do in Yellowfin Present? How can I make my presentations better using Yellowfin Story feature?

Most teams today are expected to move faster and be data-driven, but getting clear answers about performance is still harder than it should be. Even simple questions often require jumping between dashboards, piecing together insights manually, or relying on a small group of data experts to dig in. The process can be slow, and it often leads to more questions than answers.

For too long, the Model Context Protocol (MCP) has operated on a principle of open access: connect an AI agent to an MCP server, and it gets access to every single tool that server offers. While this approach is simple for initial experimentation, it quickly becomes a liability in production.

An enterprise API strategy is no longer an optional IT exercise but a mandate for modern business survival. In the digital economy, your organization's internal connectivity, or lack thereof, determines your speed, agility, and capacity for innovation. This cookbook provides the eight essential ingredients for translating technology investment into clear business outcomes, focusing the C-Suite on value, not code.

The world of Salesforce is changing fast and so is the job of Quality Assurance (QA). It used to be that QA was just the team that checked if a new feature worked correctly right before it went live. Think of them as the final proofreaders. But with powerful new tools like Agentforce (Salesforce’s smart agent system) and a huge focus on Data 360 (getting all your data in one trusted place), QA has become something much more important: the main way your company avoids major problems.