Large Language Models keep getting better, and they keep getting pricier and slower at the top end. If you are shipping anything on GPT-5 or Claude, the reasoning-grade models cost real money per token and they are not fast. For most teams I talk to, inference has...
The phenomenon of modernization in financial services in the recent decades has been largely attributed to technology transfers. Shift workloads to non legacy platforms. Avoid any proprietary middlewares and stick to APIs. Break up monolithic apps into services. Adopt...
I built a prototype for a natural language query agent a few months ago. It basically revolves around you typing a business question in plain English and getting an answer right out of the data platform. I was thinking that the main challenge of such project would be...
Most personalization systems start out simple, and they should. A scheduled job computes recommendations overnight, writes them to a table, and an API serves them on request. It is cheap, predictable, and for a lot of products it is entirely good enough. The problem...
It’s easy to get caught up in the excitement of doing WAY more in less time. Work that once required days of data cleaning, analysis, modeling, presentation building, and insight development can now be delivered in hours with AI. Managers want faster results, teams...
Everyone’s racing to get AI to “automate insights” right now. But honestly, after sitting through too many quarterly business reviews where everything looked flawless on paper, I’m starting to wonder if we’re missing the point. When Data Lies One meeting really sticks...
The insurance organizations have a very special niche in the world of data. In sharp contrast to most other fields where data related to financial information or information about personal identity is processed individually, insurers are used to processing both...
Optimizing SaaS Customer Lifetime Value (CLTV) requires continuous collection and monitoring of customer behavior data. Traditional data science pipelines lack scalability due to manual feature engineering and misalignment between transactional and analytical...
AI agents are on the rise, and it’s quickly shifting from a buzz word to reality. Development of agentic systems is fast moving from research labs and demos to production systems that can plan, act and learn from user workflows. The large language models (LLMs) that...
Consumer health products are developed or formulated based on marketing trends, trending “hero” ingredients, supplier stock formulations, and/or formulation expert subjectivity, and sometimes research. While these ways have historically made some market...