Scrumman gives Scrum Masters an evidence-grounded operating layer across work tracking, engineering, knowledge and meeting sources. It prepares ceremonies, surfaces risks, follows actions and helps you decide what needs attention next.
Governed agents can handle routine work with approvals, policy checks and audit trails, while Team Graph and coaching memory preserve context across sprints.
Built with privacy boundaries, metadata-first observability and evaluation-driven model routing—so AI assistance stays explainable, governable and cost-aware.
Scrumman is designed around a simple idea: a Scrum Master should not have to manually reconstruct project state from tickets, pull requests, documents, meetings and chat before deciding what to do next.
Connect work, engineering, knowledge and meeting evidence into a source-rooted view of delivery state, relationships and follow-through.
Benefit: less manual status reconstruction.Prepare Daily Scrum, planning, review, refinement and retrospective context with the changes, risks, decisions and open actions that matter.
Benefit: walk into ceremonies prepared.Surface stale work, delivery risk, unresolved impediments and recurring constraints with evidence that explains why they need attention.
Benefit: detect problems earlier.Carry actions and recurring patterns across sprints so coaching does not reset at the end of every ceremony.
Benefit: stronger follow-through over time.Let agents assist with routine actions while approvals, action policies and audit history keep consequential changes under human control.
Benefit: automate without giving up control.Track agent performance, latency, cost, approvals and coaching outcomes such as completed actions, resolved impediments and recurring issues.
Benefit: measure whether AI is actually helping.Scrumman strengthens the full path from evidence collection to recommendation, governed action, evaluation and operational measurement.
A common gateway standardizes model access, structured handling and task-aware routing across Scrumman workflows.
Different work can use different capability tiers, with explicit routing rather than one model being forced onto every task.
Live evaluations and structured checks verify important AI behavior before routing changes are approved.
Recommendations can be grounded back to source evidence instead of relying on isolated prompt context.
Actions can be created, approved, tracked and reconciled so recommendations do not disappear after the conversation ends.
Team memory and recurring-pattern detection preserve useful context across ceremonies and sprint boundaries.
Human approval and policy checks separate advice from consequential external actions.
See what agents did, what required approval, what succeeded or failed, and which evidence or route supported the action.
Scoped retrieval and controlled tracing reduce unnecessary exposure while preserving the metadata needed for observability.
Monitor success, failure, latency, cost and approval behavior across workflows, models and integrations.
Measure completed actions, resolved impediments, recurring issues and follow-through rather than counting AI messages.
Cheaper model routes are promoted only when real evaluation shows quality remains within the configured tolerance.
Delivery work contains judgment, context, trust, conflict and emotion. Scrumman is built to make evidence easier to see, routine work easier to govern and coaching attention easier to focus—while the human remains responsible for the team.
Connect the systems where work, code, knowledge, team communication, calendars and meetings actually live, with source-aware normalization and bounded retrieval.
Jira Cloud, Azure DevOps and Linear workflows can feed normalized work evidence into the same project context.
GitHub, GitLab and Bitbucket evidence can connect code activity, pull or merge requests and delivery signals back to work.
Confluence, Notion and Google Drive provide controlled access to project knowledge and supporting documentation.
Slack and Microsoft Teams connect team conversations, delivery signals, follow-ups and actions back to the work.
Google Meet, Microsoft Teams meetings, Zoom, Google Calendar and Microsoft Calendar can provide ceremony context, schedules, decisions and follow-up where configured.
Use project evidence, open actions, risks and recent changes to prepare the conversation—then carry decisions and follow-ups forward instead of losing them between meetings.
Daily Scrum
Backlog Refinement
Sprint Planning
Sprint Review
Retrospective
Start free, then upgrade as your connected work trackers and AI usage grow.
A work-tracker connection can be a Jira Cloud site, an Azure DevOps project, or a Linear workspace. Scrumman also integrates with Slack, GitHub, GitLab, Bitbucket, Confluence, Notion, Google Drive, Google Calendar and Meet, Microsoft Calendar and Teams, and Zoom.
For trying Scrumman with one connected work-tracker source.
For individual Scrum Masters managing a small setup.
For Scrum Masters managing multiple teams or delivery streams.
For larger teams needing broader integration coverage and AI usage.
For organizations with strict security, network, compliance or data-residency requirements, Scrumman can be scoped as an on-premise or private-cloud customization instead of the shared SaaS service.
Deployment architecture, integrations, capacity, support and security controls are reviewed with your team and quoted based on requirements.
An updated walkthrough will cover integrations, Ask Scrumman, AI workflows and governed agentic capabilities.
Updated product walkthrough coming soon.