Unleash the full potential of your data.
Let’s talk about something nobody wants to admit. Your marketing team has their own copy of customer data. Sales has a different version. Product is maintaining yet another extract. Finance built their own dashboard using data they pulled last month. Each team has created their own shadow copy of
The Challenge Your team is testing OpenAI embeddings, Anthropic’s Claude, and a custom fine-tuned model. Each needs customer data in a slightly different format. The traditional approach: build three separate pipelines, each with its own failure modes and maintenance overhead. Every AI workload expects data its own way. Your
Picture this: You’re in an executive meeting. The company just acquired another business, and the CEO wants to change how you calculate monthly active users to include the new customer base. Simple request, right? “That’ll be six months,” comes the response from the data team. Six months?! To
The Challenge Your AI team has transformative ideas. Leadership approved the budget. Then reality: preparing data for AI means months of cleaning and formatting. Data scientists become data wranglers. Engineers build pipelines instead of AI features. By the time data is ready, your competitor already shipped. The problem isn’t
Why AI is exposing decades of accepted dysfunction You can’t move at AI velocity when your data team still says “that’ll take six months.” Here’s how an entire industry normalized broken patterns, and why AI is forcing us to finally confront them. I was talking to a
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
Culture doesn't just happen. You build it. You have to be intentional. Patrick Lencioni's "The Advantage" shaped how I think about culture. Values have to be real, not aspirational. They have to mean something. They can't be corporate nonsense that no one
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
December 4 at 11 a.m. PT / 2 p.m. ET Six-month data migration timelines. Projects on hold. Costs climbing. What if you could test your migration in parallel with production? Roll back mistakes without losing work? Compress months into weeks? Join us December 4 to see how Matterbeam makes
