Build your way, without the hassle.

Focus on what matters to you - designing, developing and deploying models - without worrying about the infrastructure to do it. Simply connect your data sources to Layer, pass in your Dataset, Feature and ML model definitions, and Layer builds your entities seamlessly using your existing stack.

Completely flexible.

Layer utilizes your existing data warehouses and data lakes to run computations needed to build your features.

Through "datasource" definitions, you can specify the target schemas where Layer materializes the featuresets.

Start with simple automations of your features and develop to complex pipelines giving you immense flexibility.

Your data is yours.

Layer doesn't store any of your data -- it only stores metadata and code. You own your data and Layer processes it within your computation platform.

Layer not only introduces infra agnostic pipelines to maximize your resources for high scalability, but also helps you manage the lifecycle of your Data and ML models at scale.

Continuous delivery and deployment

Create automated or reactive pipelines with Declarative MLOps to automatically build, test, and deploy your Data and ML Models at scale. Layer is designed to grow as you move from dev to production at scale.

Empower your data team