built for data engineers
Build automation pipelines in a serverless environment to significantly reduce your data processing costs.
Build event-driven data pipelines using our function and module catalog with drag & drop ease.
Seamlessly integrate ML models for pre-labeling datasets or custom functions for pre-processing.
Run compute workloads and access cloud resource with functions
NO-CODE EASE OF USE
Create custom data automation pipelines using a no-code drag-and-drop interface or through a developer-friendly Python SDK to weave together human and machine workflows. Develop your ML pipelines or create human-in-the-loop data validation to scale production.
Production pipelines capabilities
Build your own plugins with our Python SDK, including built-in triggers for running and auto-scaling functions. Bootstrap and manage plugins using our interactive CLI, including auto-completion of commands and parameters
Assemble event-driven automation pipelines for running pre and post processing functions, integrate models into annotation workflows, deploy models in production and introduce a human-in-the-loop for data validation
Serverless Data Applications
Build, operate and deploy automation pipelines at scale with our Kubernetes-powered environment. All compute infrastructure can be handled by us for unlimited auto-scaling
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An end-to-end cloud-based annotation platform, with embedded tools and automations for producing high-quality datasets more efficiently.
Manage, collaborate, distribute and utilize your data operations, all integrated seamlessly and managed via single point of access.