CausalIQ Ecosystem - Development Roadmap¶
At-a-glance view of development releases across the CausalIQ ecosystem
Last updated: February 01, 2026
🌟 Current Ecosystem Status¶
| Project | Current Release | Project capabilities | Detailed Roadmap |
|---|---|---|---|
| causaliq (umbrella) | 0.1 Architecture | Ecosystem architecture and development standards defined | n/a |
| causaliq-analysis | 0.2 Legacy trace | Structural graph metrics and legacy learning traces | here |
| causaliq-core | 0.3 Bayesian Networks | Utility functions, graph classes (SDG, PDAG, DAG) and Bayesian Networks | here |
| causaliq-data | 0.3 Independence Tests | Data handling, score functions and independence tests | here |
| causaliq-knowledge | 0.3 LLM Caching | LLM query and response caching | here |
| causaliq-repo-template | 1.0 Foundation | Repo template for new CausalIQ projects | n/a |
| causaliq-workflow | 0.1 Workflow Foundations | Basic workflow framework | here |
| zenodo-sync | 0.1 Foundation | Follows CausalIQ standards | tbd |
All other projects not yet released.
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¶
February 2026 - Graph averaging and LLM Knowledge¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causaliq-analysis | 0.3 Graph Averaging | 📊 Planned | Probabilistic graph averaging |
| causaliq-analysis | 0.4 Averaging Analysis | ✨ Envisaged | Basic analysis of graph averaging |
| causaliq-core | 0.4 Caching and GraphML | 📊 Planned | Generic caching and GraphML support |
| causaliq-research | 0.1 Foundation Models | 🚧 Underway | Models to support PGM paper |
| causaliq-workflow | 0.2 Knowledge Workflows | 📊 Planned | LLM graph generation workflow |
| causaliq-workflow | 0.3 Result Caching | 📊 Planned | Graph generation results cached |
| causaliq-workflow | 0.4 Analysis Workflows | 📊 Planned | Graph evaluation and averaging workflows |
Code migrated from legacy monolithic repo will be modified to meet CausalIQ quality standards.
CausalIQ packages will implement the CausalIQAction interface and therefore can be included in CausalIQ Workflows
March 2026 - LLM Context and Averaging Evaluation¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causaliq-analysis | 0.5 Non-reference Evaluation | ✨ Envisaged | Evaluation that does not require reference graphs |
| causaliq-knowledge | 0.4 LLM Context | ✨ Envisaged | Variable, domain and literature context |
April 2026 - Graph Averaging Analysis¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causaliq-analysis | 0.6 Analysis Plots | ✨ Envisaged | Based on January Experience |
| causaliq-discovery | 0.1 Discovery Foundations | ✨ Envisaged | Migration of HC/Tabu-Stable |
| causal-predict | 0.1 Foundation Inference | ✨ Envisaged | Basic PyAgrum Inference |
| causaliq-workflow | 0.5 Enhanced Workflow | 🔄 Background | Comparison and dry-run capability |
Q2 2026 - Graph Averaging Production¶
| Project | Release | Status | Key Deliverables |
|---|---|---|---|
| causaliq-knowledge | 0.5 Advanced Queries | ✨ Envisaged | Based on January Experience |
H2 2026 - Complete Legacy Support¶
🚀 Future Vision Post 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.