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Roadmap
This roadmap outlines the planned evolution of MailIntel AI.
The project follows an incremental development approach, where each release focuses on improving functionality, usability, and enterprise readiness while preserving explainability and maintainability.
Future development will continue to prioritize:
- Explainable investigations
- Modular architecture
- Security by design
- Reproducible analysis
- Enterprise-grade engineering practices
- RFC822 (.eml) email parsing
- Investigation workflow
- Authentication analysis
- URL intelligence
- Language intelligence
- Evidence collection
- Explainable risk scoring
- Executive PDF reports
- JSON investigation reports
- Investigation summary
- Recommendations
- Interactive Streamlit dashboard
- Report downloads
- Investigation overview
- Docker support
- GitHub Actions CI
- Automated testing
- MyPy type checking
- Ruff linting and formatting
- Professional documentation
- Batch email investigation
- ZIP upload support
- Investigation history
- Improved recommendations
- HTML reports
- DOCX export
- CSV export
- Better visualizations
- Investigation timeline
- Search and filtering
- Domain reputation lookup
- WHOIS information
- DNS enrichment
- URL categorization
- IOC extraction
- HTML email inspection
- Header visualization
- Message threading
- Attachment metadata
MailIntel AI evolves from a standalone investigation tool into a collaborative investigation platform.
- FastAPI REST API
- Background task processing
- PostgreSQL database
- Redis caching
- React web application
- Authentication
- User profiles
- Case dashboard
- Saved investigations
- Team collaboration
- Investigation notes
- Case management
Optional AI capabilities while maintaining explainability.
Examples:
- Finding summarization
- Investigation explanations
- Executive report drafting
- Natural language search
All AI-generated content will remain clearly distinguishable from rule-based findings.
Enterprise capabilities under consideration include:
- Multi-user deployments
- Role-based access control
- Audit logging
- LDAP / SSO integration
- Threat intelligence feeds
- SIEM integration
- Investigation APIs
- Scheduled investigations
Potential research directions include:
- Explainable AI for phishing detection
- Knowledge graph-based investigations
- Graph visualization of email relationships
- Behavioral risk scoring
- Adaptive evidence weighting
- Large Language Model integration
- Multi-modal email analysis
Contributions are welcome in areas such as:
- Documentation
- Testing
- Bug fixes
- New intelligence modules
- Reporting enhancements
- User interface improvements
Please review the Developer Guide before contributing.
MailIntel AI aims to become an open, modular, and explainable email investigation platform suitable for:
- Security Operations Centers (SOC)
- Incident response teams
- Security researchers
- Digital forensics practitioners
- Educational institutions
The long-term goal is to provide transparent investigative tooling that balances automation with human oversight, enabling analysts to understand not only the outcome of an investigation but also the evidence and reasoning behind it.
Every release should satisfy three criteria:
- Stable and reproducible.
- Fully documented.
- Backed by automated testing.
Quality is prioritized over release frequency to ensure that each version remains dependable for users and contributors.