The Challenge Your product team wants to test RAG with three different vector databases, compare embedding models, and experiment with chunking strategies. Each variation means filing engineering tickets. Engineering backlogs measure in quarters. By the time you test approach No. 2, your competitor already shipped the winning solution. AI innovation
A ritual playing out in boardrooms everywhere: the new data strategy presentation. This time it’s different. This time we’ll capture the value. The slides are beautiful. The architecture diagrams are comprehensive. Everyone nods. Nobody believes it. We’ve been here before. At least three times, in fact. The
And we're all just pretending it's going to work out fine A data scientist told me something that perfectly captures our industry's delusion: "I spend most of my time wrangling data. I can't trust my data engineers because they don'
A behind-the-scenes look at building AI infrastructure with Promoboxx We've been having a lot of conversations lately that start the same way: "We want to experiment with AI, but our data infrastructure is slowing us down. We're wasting all our time on $#&%!* pipelines instead
There’s a moment we kept seeing at ODSC East last week. Someone would be walking by, scanning booths like we all do at conferences—half-looking for free stuff, half-trying to avoid eye contact—and then they’d stop. Dead in their tracks. Not for a t-shirt. Not for a
The developments of generative AI in the past few years have been amazing. There are promises of AI agents revolutionizing everything from customer service to software development. Now they're coming for your data infrastructure. The pitch is seductive: AI agents will automatically handle data integration, quality, and governance.
