Encord
Best For
Machine learning teams needing to curate high-quality training data and manage the model development lifecycle for computer vision.
Not Ideal For
Individual hobbyists or small teams looking for a simple, manual image cropping tool without AI automation.
Pros & Cons
- Powerful AI-assisted labeling for video and medical imaging (DICOM/NIfTI)
- Comprehensive quality control workflows and performance tracking
- Active learning loops to prioritize data that improves model performance
- Robust API and SDK for seamless integration into ML pipelines
- Support for complex multimodal data including SAR and thermal imagery
- Steep learning curve for non-technical users
- Pricing is opaque and geared toward enterprise-scale budgets
- Initial setup and ontology configuration can be time-consuming
Key Features
Encord Annotate
Automated labeling platform for images, videos, and specialized formats like DICOM.
Encord Index
A data management tool to visualize, search, and curate datasets before labeling.
Active Learning
Automated workflows that identify edge cases and high-value data to label next.
Quality Management
Built-in review cycles, consensus scoring, and annotator performance analytics.
AI Assisted Labeling
Uses segment-anything models and object tracking to speed up manual annotation by up to 10x.
Pricing Breakdown
- pro
- Custom pricing for scaling ML operations with advanced automation
- free
- Free trial available upon request for specific projects
- annual
- Discounts available for multi-year or annual commitments
- starter
- Custom pricing for small teams starting their first ML project
- enterprise
- Full platform access with SSO, dedicated support, and unlimited scale
⚠️ Pricing is subject to change. Always verify current pricing on the tool's official website before purchasing.
Free Tier
- storage
- Limited by trial agreement
- features
- Core annotation features included in trial, advanced Indexing may be restricted
- requests
- Limited by trial agreement