Workflows

Build and automate multistep data annotation projects with ease

Build and Automate Multistep
Data Annotation Projects

Workflows saves you from having to manually manage complex processes so you can spend your time on building great AI-powered products.

High-quality Training Data 20x Faster at Half the Cost

Workflows allows customers to build and automate multistep data annotation projects with ease. The simple graphical interface ensures no coding skills are required to create a workflow consisting of multiple jobs.

Customers now have access to a real data pipeline solution that reduces latency and increases efficiency via automated data routing. Break down complex data annotation projects into smaller, easier tasks, then enjoy greater control over customization of job designs and contributor channels at each step.

Workflows Delivers:

Lower Costs at Scale

Combine human annotation with machine learning to deliver large volumes of annotated data up to 20 times faster at up to 50% lower cost, easily allowing you to scale your AI initiatives.

Plug and Play

Workflows uses a graphical user interface to enable anyone, regardless of skill, to configure operators with flexible routing rules. This eliminates reliance on limited technical resources and ensures the most important rows are annotated to your specifications.

Automated Data Pipeline Via API

Once you set up a workflow, leverage our Workflows API to programmatically send new data and conveniently obtain results in real time.

Enhanced Quality Control for
Annotation Projects

Easily break jobs into small tasks with no coding necessary, and complete jobs faster by automating the data routing between operators, reducing the rate of human error. Optimize the quality of your annotations through the ability to customize and target contributors for every task.

Automation and Increased
Efficiency

Automate data routing and the aggregation of results in a single report, eliminating the latency caused by manual labor and jobs that need to be run sequentially.