Feature pipelines without the plumbing
Build, transform, and export ML features without writing data pipeline code.
The problem
Data scientists spend more time building data pipelines than training models. Manual data preparation and feature engineering create bottlenecks that slow down model development.
Exporting features to vector databases requires custom scripts and ongoing maintenance. Each new data source or transformation adds complexity and technical debt.
Without proper lineage tracking, it's difficult to understand how features were created or reproduce experiments reliably.
The RulzAI solution
Connect blob storage → Clean and transform → Enrich features → Export to vector DB (Qdrant, Pinecone) → Track lineage
Automated feature pipelines
Export to vector databases (Qdrant, Pinecone)
Data lineage tracking
No manual data prep
Outcomes
Faster model iteration
Governed lineage
Clean feature stores