TeamSync AI turns your board — tasks, assignees, dependencies and discussion — into a knowledge graph, computes six kinds of coordination risk from it, and shows the tasks and people behind every warning. It suggests the fix, and tells you mid-sprint when the plan will not make its deadline.
A task board, and an analysis you can check rather than take on trust.
Delay, workload, knowledge concentration, dependencies, coordination and silent members — computed from your project's own graph, the same way every time.
Every finding names the tasks and people it rests on, so a warning can be verified or challenged, not just believed.
Workload recommendations come with the reassignments that carry them out and their predicted effect. Apply one, re-run, and see what changed.
Compares work done with time elapsed and warns while the sprint is still running, not after it has slipped.
Kanban with sprints, components, blocking dependencies (cycles refused) and task discussion.
Owner, admin, project manager, developer and viewer — checked by the API on every request, not just hidden in the interface.
The numbers come from the graph. A language model, if you configure one, only puts them into words.
Tasks, assignees, story points, sprints, dependencies and comments — the data your team already keeps.
Critical paths, single owners, load skew and pace are graph calculations: no language model decides whether a risk exists.
Each warning cites what it rests on and suggests what to do. A language model is optional and only narrates.
Evaluated on real Jira histories from open-source projects (the TAWOS dataset).
0.79
AUC at the halfway point of a sprint, on 22 projects the system had never seen
487×
fewer tokens than sending the whole project to a language model, at 2,003 tasks
200/200
fabricated citations caught and removed before reaching the user
Create a project, add your tasks and team, and run the analysis.
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