Engineering deep-dives, case studies, and lessons learned from building data and AI systems at scale.
How we helped a Fortune 500 healthcare company migrate from batch processing to real-time streaming — processing 2 billion events per day with sub-second latency.
Lessons learned from fine-tuning 20+ models across industries — what works, what doesn't, and how to avoid the most common pitfalls.
A five-level framework for assessing your ML infrastructure maturity — from ad-hoc notebooks to fully automated, self-healing ML systems.