Continuous Improvement
EvidAI continuously evolves and improves through aggregated learning, research advances, and user feedback.
How We Improve
Aggregated Learning
From platform-wide usage (anonymized):
- Common correction patterns
- Error type identification
- Accuracy benchmarking
- Performance optimization
Research Integration
We stay current with:
- Latest methodology standards
- New assessment tools
- Emerging best practices
- Research community feedback
User Feedback
Direct input through:
- Feature requests
- Bug reports
- Improvement suggestions
- Support interactions
What Gets Better
Accuracy Improvements
- Screening predictions
- Extraction accuracy
- Quality assessments
- Relevance rankings
Feature Enhancements
- New capabilities
- Improved interfaces
- Additional integrations
- Enhanced workflows
Performance Gains
- Faster processing
- Better efficiency
- Reduced errors
- Improved reliability
Privacy Protection
What We Don't Access
Your data remains private:
- Individual study content
- Specific review details
- Personal information
- Identifiable decisions
What We Learn From
Anonymized, aggregated patterns:
- Decision type distributions
- Correction frequencies
- Feature usage patterns
- Performance metrics
Update Delivery
Automatic Updates
- Core improvements automatic
- No action required
- Seamless integration
- Zero downtime
Feature Releases
- Regular capability additions
- Announced in advance
- Documentation updated
- Training provided
Your Role
Contributing to Improvement
Help us improve by:
- Making corrections when needed
- Reporting issues promptly
- Providing feedback
- Participating in surveys
Staying Updated
Keep current by:
- Reading release notes
- Exploring new features
- Attending webinars
- Checking documentation
Enterprise Options
Custom Training
Enterprise users can:
- Train on specialty content
- Customize models
- Define domain priorities
- Maintain private improvements
Feedback Channels
Enhanced enterprise access:
- Dedicated support
- Feature prioritization
- Custom development
- Advisory participation