Data preparation for AI is far more complex than it is for traditional data platforms. Success depends not only on storage or throughput, but also on data quality, lineage, governance, and pipelines that support both training and real-time inference. The gap between experimentation and production remains one of the biggest reasons AI projects get stuck […] The post From the AI Trenches: Lessons Learned Building Infrastructure for AI-Ready Data appeared first on lakeFS .