Artificial intelligence is changing how every team, from startups to global brands, builds, learns, and competes. But AI is only as powerful as the data it’s built on. That’s why we’ve rebuilt Countly from the ground up, to make data faster, smarter, and truly AI-ready.With Countly 26.01, we’re introducing our next-generation data engine: This release marks a turning point for Countly: from analytics to intelligence.

In an era of economic uncertainty and rapid digital transformation, finance and accounting professionals face a paradox: their data has never been more abundant, yet access to it has never been more challenging. Kevin Gibson, CPA and Principal Solutions Engineer at insightsoftware, recently sat down with Scott Taylor on an episode of the Don’t Panic!

As artificial intelligence (AI) adoption has grown over the last several years, it has become increasingly clear to companies and observers that successful AI requires real-time data and context. And it’s not just AI—every critical business function that relies on data inputs needs that data to be as trustworthy and fresh as possible.

Better audience data means better ROAS, and ClickUp demonstrated this using Census to enhance ad performance, personalization, and cross-channel consistency.

When was the last time your analytics team waited hours—or even days—for updated data? Or your development environment fell so far behind production that testing became guesswork rather than validation? For IT leaders managing distributed systems, the challenge isn’t moving data once. It’s keeping every environment that depends on that data perfectly aligned as schemas evolve, records multiply, and business requirements shift. Manual scripts break. Full refreshes waste resources.

Wealth management has always been about personal touch. Relationship managers provide a white-glove service to elite clientele - guiding investments, financial plans, and more. However, they’re under growing pressure to serve more clients and drive bank revenue, without diluting that personal connection and service quality. This dual mandate is placing relationship managers in a catch-22 situation. If they serve more clients their ability to provide personalized services diminishes, and vice versa.

Discover how Smartify uses a warehouse‑first, reverse ETL strategy to personalize user engagement and turn data into meaningful product conversions for millions of art lovers.