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...
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...
Save $500K–$1M Annually on Each LLM Project with Cake
Teams running LLM projects on Cake's platform are realizing significant cost advantages, saving between $500K and $1M annually per project. These...
Deploy AI Models to Production Nearly 4X Faster with Cake
Enterprises using Cake have achieved up to 3.9x faster deployment of AI models into production, moving from months of setup to just weeks....
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6x MLOps Productivity: How Teams Do More With Less Using Cake
Enterprises running on Cake have seen up to a 6x increase in MLOps productivity. That's not marketing spin. It's a direct outcome of teams...
Anomaly Detection with AI & ML: A Practical Guide
When we think of business problems, we often picture the big, obvious ones: a website crash or a major security breach. While those are critical, the...
AIOps vs. MLOps vs. DevOps: Clarifying the Differences
Are your IT teams constantly fighting fires? Are your machine learning (ML) projects stuck in the lab, struggling to make it into production? These...
How to Establish an Effective AIOps Framework
Your IT team is likely drowning in a sea of alerts. It’s a constant battle, trying to figure out which notifications are critical and which are just...
