Encord Blog
How to Create Workflows in Encord
Alexandre Bonnet, Solutions Engineer at Encord, walks through our latest feature: Workflows.
Workflows allow ML teams to build fully customizable and automated ML pipelines to improve the efficiency of creating high-quality training data.
Workflows are easy to create:
- Step 1: Choose from the library of 6 components (Start, Annotate, Router, Review, Archive, Complete)
- Step 2: Assign Annotators and Reviewers
- Step 3: Create arbitrarily complex workflows
Power your AI models with the right data
Automate your data curation, annotation and label validation workflows.
Get startedWritten by
Alexandre Bonnet
Explore our products
Index
Manage & curate your data
Understand and manage your visual data, prioritize data for labeling, and initiate active learning pipelines.
Annotate
Supporting your labeling needs
Super charge your data annotation with AI-powered labeling — including automated interpolation, object detection and ML-based quality control.
Active
Find & fix data issues with ease
Monitor, troubleshoot, and evaluate the data and labels impacting model performance.
Software To Help You Turn Your Data Into AI
Forget fragmented workflows, annotation tools, and Notebooks for building AI applications. Encord Data Engine accelerates every step of taking your model into production.