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The world is continuously changing and so is your data. Keeping your features and datasets up to date is essential to maximize their value. Layer automates this with regular builds.
Once you define the correctness criteria and tests, Layer ensures that the data and the pipelines keep conforming to your rules. In case of an error, you can quickly see and dig through it.
Layer automatically keeps track of the characteristics and statistics of your data to to provide a quick yet informative overview.
Layer keeps track of the dependency graph between your datasets, features, and ML Models. It keeps the pipelines up-to-date by triggering builds (scheduled, reactive or manual) whenever needed without any babysitting. It's so simple that your data team can forget it after setting it.
Layer’s automatically tracks your data characteristics to alert you to drifts in data or drops in data quality. It can be set to trigger rebuilds when data drops, retrains of models, and offer manual solutions lie removing features from the input set.
Centralized location for AI management across the enterprise, as well as a way to identify any duplication of efforts and opportunities for cost savings
Easy way to access performance
and audit logs for compliance purposes
Role-based access controls and better approach for managing AI security