Robust dataset tracking and management for ML/AI teams

Streamline your machine learning workflows with powerful dataset versioning, metadata tracking, and lineage analysis

Version-controlled datasets

Metadata and quality insights

Full dataset lineage

Collaborate and reuse

Version-controlled datasets

Track every version of your datasets and keep a clear record of changes.

With Kiroframe, you can:

Compare dataset versions side-by-side
Roll back to previous versions
Automatically record who changed what and when

Easily link each dataset version to the training jobs and model artifacts, ensuring full traceability and better reproducibility of ML experiments.

Metadata and quality insights

Automatically collect metadata like schema, column types, null values, and data distribution.

Set alerts and thresholds to identify data drift or broken datasets early

Kiroframe detects schema changes over time and supports quality dashboards for monitoring dataset health, enabling teams to catch and resolve issues early.

Full dataset lineage

Visualize how datasets flow through your ML pipeline: from ingestion to training, evaluation, and deployment.

Kiroframe lets you trace the exact datasets used for each model or experiment.

Dataset lineage spans ingestion, transformations, training, and model usage, helping your team debug complex workflows and ensure regulatory compliance.

Collaborate and reuse

Centralize dataset storage and sharing between teams.

Use tags and metadata filters to quickly find relevant datasets for reuse.

Enable role-based access, dataset tagging, and comment threads to foster collaboration and avoid duplicated effort.

Robust dataset tracking and management for ML/AI teams

Version-controlled datasets

Metadata and quality insights

Full dataset lineage

Collaborate and reuse

Supported platforms