Find and fix the flaws in your AI training data.
What is Encord Active?
Encord Active is an open-source platform designed to evaluate and improve the quality of datasets used for training machine learning models. It enables users to systematically analyze their data, identify potential issues like label errors or imbalances, and curate higher-quality datasets. The tool focuses on computer vision applications, working with images and videos.
The platform operates by ingesting a user’s labeled dataset and automatically computing a range of metrics related to data and label quality. Users interact with it through a visual interface to explore these metrics, filter data based on specific criteria, and prioritize samples for review. The team behind the official website developed this system to help practitioners diagnose problems within their data before model training, aiming to build more reliable and performant AI models.
Key Findings
- Data Quality: Identifies and fixes dataset issues to improve model accuracy and performance significantly.
- Model Evaluation: Measures model performance across key metrics to pinpoint strengths and weaknesses clearly.
- Visual Exploration: Interactively explores datasets and model predictions through intuitive charts and visual tools.
- Automated Insights: Discovers hidden patterns and data issues automatically to accelerate the research cycle.
- Active Learning: Prioritizes the most valuable data for labeling to optimize annotation budgets efficiently.
- Collaboration Tools: Enables teams to share findings and annotations seamlessly within a unified platform.
- Performance Monitoring: Tracks model degradation and data drift over time to maintain reliable deployments.
- Workflow Integration: Connects directly with labeling tools and ML pipelines for a smooth process.
- Comprehensive Reporting: Generates detailed reports on data health and model metrics for stakeholder review.
- Customizable Dashboards: Builds tailored views to monitor specific project metrics and KPIs effectively.
Who is it for?
Programmer
- Model debugging
- Dataset quality assessment
- Automated error discovery
- Performance bottleneck analysis
- Collaborative review workflow
Project Manager
- Monitoring annotation progress
- Client deliverable validation
- Stakeholder reporting
- Issue prioritization triage
- Milestone verification
Manufacturing Supervisor
- Visual inspection model audit
- Training data curation
- Supplier quality analysis
- New defect documentation
- Process compliance check
Pricing
Starter @ Get started
- Image and video annotation toolkit
- Complex and dynamic ontologies
- Customizable workflows
- Self-serve support
- Up to 500k data volume
- Up to 50k Active data volume
Team @ Get started
- Data agents
- Performance analytics
- Model evaluation
- Onboarding support
- Up to 100m data volume
- Up to 1m Active data volume
Enterprise @ Contact sales
- Multiple workspaces
- Single sign-on (SSO)
- Enterprise SLA and support
- VPC and on-prem deployments
- 1bn+ data volume
- Up to 10m Active data volume