It's a bit like evolution in action. Every software or system you adopt solves a problem — until the environment changes. And in 2025, the environment has definitely changed.

Ever feel like there's some critical piece of information that you just can't find? Data should be a strategic advantage. It's supposed to fuel smarter decisions, drive customer satisfaction, and reveal new revenue opportunities.

ETL and other data remodeling projects are quite possibly the biggest blockers of AI agent development. According to BCG, 74% of organizations struggle to achieve value from their AI initiatives.

Hansel and Gretel had it easy. They were only lost in the woods once. Modern teams, on the other hand, have to worry about having their time eaten by a continual hunt through a corporate data wilderness.

It's time to stop searching in a foreign language. Working with computers forces people to think like a computer and communicate in a language the computer understands.

There's a common misconception in enterprise AI: if your AI agent needs access to internal knowledge, you first need to build a vector database. It sounds logical until you actually try it.

We are surrounded by devices that give us instant connectivity to all the world's knowledge, and we still can't find answers to simple questions. It's ironic, and it gets worse when you try to find internal company information.

It's ironic: we are surrounded by devices that give us instant connectivity to all the world's knowledge, and we can't find answers to simple questions. Internal search is even harder, and the problem is only getting worse.

AI agents sound extremely impressive: autonomous actors that can use independent reasoning and planning to carry out instructions, make decisions, and perform certain actions — all without user involvement.