Systems | Development | Analytics | API | Testing

Large language models (LLMs) can transform how businesses interact with data, but connecting them directly to databases presents serious risks. Security concerns include credential exposure, SQL injection, and the "Confused Deputy" problem, where elevated AI privileges bypass user permissions. Since LLMs lack built-in authorization, securing access requires external measures. Here’s how to protect your databases when integrating LLMs.

Enable teams to move from source systems to AI-driven insights without custom ingestion code or infrastructure management.

Your finance team wastes 14 days every month on manual consolidation. Your close stretches to 15-25 days. And you're one key person departing from chaos. The brutal math: Your "free" Excel process actually costs $850K+ annually in wasted time, errors, and missed opportunities. Meanwhile, leading multi-entity CFOs just cut their close time by 80% and freed their teams for strategic work instead of reconciliation hell.

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.