An interactive workbench for dataset intelligence.
Most of the work of machine learning is the work of datasets — finding, building, cleaning, refining, verifying, combining. Most tools treat this as a precursor to the real work.
ALEX is built on the opposite premise. It is a dedicated environment for dataset work, with a GUI designed for the analyst, the researcher, and the engineer who actually do it.
Build datasets from scratch. Keep records of many in parallel. Combine sources into entirely new collections. Verify integrity end to end.
Ingest from files, folders, APIs, or live sources. Apply schemas. Tag, annotate, and version with full lineage.
Detect duplicates, missing values, distribution anomalies, and labelling inconsistencies — visually, before training.
Iterative subset construction with side-by-side comparison. Save, branch, and audit every refinement.
Distribution views, class-balance diagnostics, embedding-space exploration, drift detection over time.
Run integrity checks against custom rules. Catch the problems that will not show up until training fails three weeks in.
Combine multiple existing datasets into custom collections with conflict resolution and provenance preserved.
ALEX is deployed on customer infrastructure. We work with each team to configure it for their data, their workflows, and their compliance requirements.