RationaleHub

RationaleHub is a web app (with optional desktop agent) that captures, standardizes, and audits model explanations across teams and tools. Instead of dumping SHAP plots into slide decks, it forces every prediction to have a structured “decision record”: input snapshot, explanation artifacts (attribution, counterfactual, example-based), confidence/uncertainty, and a human-readable rationale template tied to policy requirements (e.g., lending adverse action reasons). It integrates with common ML stacks via an SDK and stores explanation runs in a searchable registry with versioning, lineage, and approval workflows. Reviewers can compare explanations across model versions, detect drift in top reasons, and flag cases where explanations are unstable or non-actionable. It’s not magic: it won’t make black boxes transparent, but it will make explanation practices consistent, auditable, and easier to defend to internal risk, legal, and regulators.