Product Roadmap
Discover what's coming next to CloudExplain. We're building advanced features to make AI explainability more collaborative, insightful, and comprehensive than ever before.
Making AI explainability collaborative, causal, and comprehensive for teams and organizations worldwide.
CloudExplain is evolving beyond individual model explanations to become a comprehensive platform where teams can collaborate on understanding AI behavior, discover causal relationships, and gain deeper insights through advanced analytics and multi-source data integration.
Development Timeline
Reconstruct causal graphs to understand which features influence which others
Key Features:
Collaborate on insights, share with your team, discuss and like results, and propose new hypotheses
Key Features:
Discover which subgroups of your data behave differently and understand WHY using XAI and causal analysis
Key Features:
Leverage various connected data sources to understand feature connections and discover missed insights
Key Features:
Feature Deep Dives
Go beyond correlation to understand true causal relationships in your models
Our causal analysis engine will automatically reconstruct causal graphs from your data, helping you understand not just which features are important, but how they influence each other and the final predictions.
What You'll Get:
- • Visual causal graphs with edge weights
- • Identification of confounding variables
- • Direct vs indirect effect analysis
- • Counterfactual scenario modeling
Use Cases:
- • Policy intervention planning
- • Root cause analysis
- • Feature engineering optimization
- • Bias detection and mitigation
Transform AI explainability from a solo activity into a collaborative team effort
Enable your entire team to collaborate on understanding AI models. Share insights, discuss findings, propose hypotheses, and build collective intelligence around your AI systems.
Share & Discuss
Share explanations with team members and start discussions around findings
Comment & Rate
Add comments to specific insights and rate the quality of explanations
Propose Hypotheses
Suggest new hypotheses and track their validation across experiments
Automatically discover and understand subgroups that behave differently in your data
Our advanced subgroup detection algorithms will automatically identify segments of your data where the model behaves differently, then use XAI and causal analysis to explain why these differences occur.
Connect multiple data sources to discover hidden relationships and missing insights
Integrate data from multiple sources to get a complete picture of feature relationships. Our system will suggest connections you might have missed and recommend additional data that could improve your models.
Supported Integrations:
- • SQL databases (PostgreSQL, MySQL, SQL Server)
- • Data warehouses (Snowflake, BigQuery, Redshift)
- • Cloud storage (S3, Azure Blob, GCS)
- • APIs and real-time data streams
Intelligent Insights:
- • Cross-source correlation analysis
- • Missing feature recommendations
- • Data quality issue detection
- • Temporal pattern discovery
Help shape the future of CloudExplain by sharing your feedback and feature requests
We believe the best products are built with community input. Share your thoughts on our roadmap, suggest new features, or let us know about your specific use cases.
Stay Updated
Follow our progress and be the first to know when new features are released. We'll keep you updated on our development milestones and beta testing opportunities.