CausalIQ Ecosystem - Development Roadmap¶
At-a-glance view of development releases across the CausalIQ ecosystem
Last updated: December 04, 2025
🌟 Current Ecosystem Status¶
| Project | Current Release | Project capabilities | Detailed Roadmap |
|---|---|---|---|
| causaliq (Main) | 0.1 Architecture | Architecture and development standards defined | n/a |
| causaliq-workflow | 0.2 Basic CLI | Basic CLI with real-time execution feedback | here |
| causaliq-core | 0.2 Graphs | Utility functions and graph classes (SDG, PDAG, DAG) | tbd |
| zenodo-sync | 0.1 Foundation | Follows CausalIQ standards | tbd |
| causaliq-repo-template | 1.0 Foundation | Defines standardised project docs, structure and CI testing | n/a |
All other projects not yet started.
Milestones:
- end-March 2026: CausalIQ LLM-assisted model-averaging experiments & results for conference paper
- end-April 2026: Charts and Tables for CausalIQ LLM-assisted model-averaging paper
- end-September 2026: Experiments and results for another paper
- end-2026: Full reproducibility of key published papers with assets on Zenodo
📊 Ecosystem Development Timeline¶
December 2025 - Monolith Migration & Graph Averaging¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causaliq-data | 0.1 Foundation Data | 📝 Planned | Data, NumPy and Pandas classes and BNFit interface |
| causaliq-core | 0.3 Bayesian Networks | 📝 Planned | BNs and i/o, using BNFit interface |
| causaliq-analysis | 0.1 Foundation | ✨ Envisaged | Action interface supported |
| causaliq-analysis | 0.2 Structural Metrics | ✨ Envisaged | Structural graph metrics from monolith |
| causaliq-analysis | 0.3 Graph Averaging | ✨ Envisaged | Probabilistic graph averaging |
| causaliq-data | 0.2 Scores | 📝 Planned | Score functions migrated with plugin architecture |
Code migrated from legacy monolithic repo will be modified to meet CausalIQ quality standards.
CausalIQ packages (excluding core) will implement the CausalIQ Action interface and therefore can be included in CausalIQ Workflows
January 2026 - LLM Causal Knowledge I¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causal-analysis | 0.4 Averaging Analysis | ✨ Envisaged | Basic analysis of graph averaging |
| causal-knowledge | 0.1 Foundation | ✨ Envisaged | Requirements and technical architecture |
| causal-knowledge | 0.2 LLM APIs | ✨ Envisaged | Some LLMs integrated |
| causal-knowledge | 0.3 Simple Edge Queries | ✨ Envisaged | Simple Edge Queries - existence/orientation |
| causal-knowledge | 0.4 Query Database | ✨ Envisaged | Query, context, response stored |
| causaliq-workflow | 0.3 Enhanced Workflow | 🔄 Background | Conservative execution and dry-run capability |
| causaliq-workflow | 0.4 Progress and Summary | 🔄 Background | Real-time progress tracking and execution summary |
| causaliq-workflow | 0.5 Advanced Features | ✨ Envisaged | Metadata, compare mode, timeouts, estimated completion |
February 2026 - LLM Causal Knowledge II¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causal-analysis | 0.4 LLM Analysis | ✨ Envisaged | Based on January Experience |
| causal-knowledge | 0.5 Advanced Queries | ✨ Envisaged | Based on January Experience |
| causaliq-papers | 0.1 Import graph | ✨ Envisaged | Import graphs from monolithic repo |
🚀 Future Vision Post February 2026¶
Research Platform Features¶
- LLM Integration: Model averaging, hypothesis generation with causal reasoning
- Web Interface: Browser-based workflow designer for non-technical researchers
- Publication Support: Reproducible research outputs with automated documentation
Advanced Capabilities¶
- Workflow Marketplace: Sharing and discovering research workflow templates
- Interactive Notebooks: Jupyter integration with workflow execution
- Multi-machine Execution: Distributed workflows across compute clusters
- AI-assisted Optimisation: Automated hyperparameter and workflow tuning
- Integration Ecosystem: Plugins for major research tools and platforms
Performance & Scale¶
- High-performance Computing: GPU acceleration for large-scale structure learning
- Distributed Storage: Cloud-native knowledge bases with global accessibility
- Real-time Analytics: Live causal discovery with streaming data sources
- Enterprise Features: Security, compliance, and enterprise-grade deployment
This roadmap is updated weekly and reflects current development priorities. For detailed project-specific roadmaps, see individual project documentation.