Why 90% of Agentic RAG Projects Fail (and How Cake Changes That)
TL;DR Most RAG projects stall at 60%: Quick demos are easy to build, but brittle architectures break down before reaching production. The last 40% takes real infrastructure: You need evaluation sets,...
Featured Posts
AI-Powered Customer Engagement in Retail: A Complete Guide
At its core, retail has always been about relationships. The best local shop owners knew their customers by name, remembered their last purchase, and...
Top AI Use Cases Revolutionizing Retail and eCommerce
Your eCommerce business is sitting on a goldmine of data. Every click, search, and purchase tells a story about your customers and your products. The...
MLOps in Retail: A Practical Guide to Applications
Think of a brilliant machine learning (ML) model as a high-performance race car engine. It’s incredibly powerful, but on its own, it can’t get you...
Time-Series Modeling for Smarter Business Predictions
Your business generates a constant stream of data: daily sales, weekly customer sign-ups, monthly expenses, etc. Too often, this information sits in...
How to Analyze Time-Series Data in Python: A Practical Intro
Every dataset collected over time tells a story. It’s a chronological narrative of your business, showing the peaks, the valleys, and the subtle...
AI Time-Series Forecasting Techniques: A Complete Guide
Your historical data is telling a story about your business. The question is, are you equipped to understand what it's saying about the future? While...
Identify & Overcome AI Pipeline Bottlenecks: A Practical Guide
Your AI pipeline should be a superhighway for data, but too often it feels like a traffic jam during rush hour. A single slowdown, or bottleneck, can...
Detecting Outliers in Time-Series Data: A Guide
Every data point tells a part of your business' story, but some shout louder than others. These are your outliers, i.e., the sudden spikes and...
