Engineering teams have more delivery data than ever, scattered across Jira boards, GitHub repositories, Monday.com workspaces, and GitLab projects. Yet they still cannot reliably say where risk is building until something breaks and impacts a deadline or a customer.
ValidFlow reads commit history and project boards to answer that question from evidence rather than gut feel. Every board gets a Data Confidence Score measuring six dimensions of data quality: workflow, ownership, dependencies, staleness, consistency, and duplicates. Every repository gets a Drag Audit surfacing delivery risk concentration and refactor ROI candidates.
The platform was built for engineering leaders in regulated organisations who need to demonstrate governance to auditors, justify tech debt investment to finance teams, and report delivery readiness to stakeholders with numbers and trends rather than narratives and estimates.
ValidFlow never stores or scans source code. It reads metadata including field values on boards, commit messages, file paths, and authorship records. It scores what it finds against configurable rules and presents the results in shareable reports. All data is hosted in the EU at AWS London and encrypted at rest and in transit.