The lakeFS Blog
As AI adoption evolves and teams advance from scattered ML trial projects to running AI as a production system, they inevitably face the question of
- Einat Orr, PhD
Modern data operations call for more than just lightning-fast queries and scalable storage. Safety, reproducibility, and control are all key parts of the equation. As
- Itai Gilo
You probably heard the saying “Garbage in, garbage out.” It holds true for any data system but properly prepared and handled data is especially critical
- Tal Sofer
The AI agent revolution is here. Coding agents like Claude Code, Cursor, and Codex are writing production software. Infrastructure agents are provisioning cloud resources. Data
- Oz Katz
Free Virtual Event for Enterprise AI Leaders Building AI that works in production is hard. For most enterprise teams, the biggest obstacle isn’t the model,
- Gottfried Sehringer
AI systems increasingly influence decisions made in financial services, healthcare, and public services. This means teams need to be able to demonstrate that their models
- Idan Novogroder
Based on my presentation at PyData Global 2025. My colleague Yoav recently wrote about why reproducibility matters so much in healthcare AI and how data
- Joe Pringle
As data quantities increase and pipelines become more complex, understanding where data originated, how it changed, and how it is used becomes increasingly important. This
- Tal Sofer
Based on my presentation at PyData Global 2025 When we – engineers – hear the word “compliance,” we tend to roll our eyes. We want
- Itai Gilo
Over the last few years, AI and machine learning have moved from research projects into the core of the medical industry. Models now influence diagnosis,
- Yoav Yetinson
Preparing data for AI projects is about more than fast storage or shiny new table formats – it all starts with selecting the right data
- Itai Gilo
