Skip to content
WorksBuddy
TARO
Automatically

Automatically Balance Team
Capacity Across Every Sprint

TARO reads active tasks and sprint capacity, then suggests exact reassignments to balance overloaded members before deadlines.

Balance Your TeamSee how it works →
Automatically
How it works

From unbalanced sprint to rebalanced team in four steps

TARO reads capacity continuously, surfacing imbalances before they become missed deadlines.

1

Scan

TARO reads every task and every member's capacity

TARO keeps a live view of every member's active task count, estimated effort, due dates, and sprint commitments. Not a snapshot from sprint planning a continuous read that updates every time a task is added, moved, or completed.

2

Detect

Identifies who's overloaded, who has room, and what's at risk

TARO flags every member carrying more than they can realistically deliver before the sprint ends, and pairs them with members who have capacity now. It also surfaces which tasks are deadline-critical, so rebalancing focuses on what matters most.

3

Suggest

Exact reassignments. Not vague advice.

TARO doesn't just say Marcus is overloaded, consider rebalancing. It tells you exactly which task to move, who to move it to, and why based on their available capacity, skill match, and the deadline risk of leaving it.

4

Apply

Accept all, pick some, or ignore. Your call.

TARO's suggestions are a starting point, not a mandate. Accept all in one click, cherry-pick what makes sense, or dismiss them. Every reassignment is logged, every decision tracked, and the capacity view updates in real time as changes apply.

  • Accept all in one click
  • Cherry pick suggestions
  • Instant board update
  • Marcus: 96% → 61%. Sprint delivered on time, no surprises.
Why Workload Distribution

Six reasons teams never go back

When TARO flags an overload on Tuesday, your lead can fix it before the deadline slips on Friday the difference between visibility and surprise..

Catch overloads before deadlines slip

Catch overloads before deadlines slip

TARO flags capacity problems while there's still time to act not after the missed deadline hits the retrospective. Tuesday visibility beats Friday surprises.

Exact reassignments, not vague warnings

Exact reassignments, not vague warnings

TARO names the task, names who to move it to, and explains why. Leads stop spending their morning working out who can absorb what TARO already did that thinking.

Balanced teams ship more consistently

Balanced teams ship more consistently

Consistently overloaded engineers burn out; underutilised ones disengage. TARO keeps the load even all the way through delivery, not just at planning.

Skill match, not just headcount

Skill match, not just headcount

TARO doesn't just find whoever has the most free capacity. It matches tasks to people with the right skills and ownership, so the person receiving it is the right choice.

Live capacity view across the whole sprint

Live capacity view across the whole sprint

The capacity dashboard updates every time a task is added, moved, or completed. Leads always have the current picture, not a stale spreadsheet from Monday's planning.

Suggestions, not mandates

Suggestions, not mandates

TARO recommends; every lead stays in control accept all, accept some, or override. The AI informs the decision, the human makes it.

Who uses it
Deepak MehrotraDeepak MehrotraDeepak MehrotraDeepak Mehrotra

800+

product teams

Built for every team running against a deadline

Engineering leads, scrum masters, and PMs use Workload Distribution differently, but all solve one problem: capacity visible early can be managed. TARO makes sure nothing becomes a Friday surprise that was knowable on Tuesday.

3×

Earlier overload detection

68%

Fewer missed sprint deadlines

1

Click to apply all reassignments

91%

Suggestions accepted by leads

Engineering Leads

Who has capacity for this bug? stops being a Slack message.

Engineering leads open TARO's capacity view and instantly see who has room, who's at risk, and which tasks are safest to move. What took 15 minutes in a standup resolves in 30 seconds, before the standup even happens.

More from TARO

Workload distribution is just the start

TARO's intelligence layer runs across the full task lifecycle, not just when things go out of balance.

Smart Task Creation

Type one sentence. TARO generates a fully structured task title, description, priority, due date, and assignee in under 3 seconds. No forms, no clicks.

Risk Analytics

TARO tracks overdue tasks, blocked dependencies, and sprint velocity trends, surfacing which tasks are most likely to slip before they do.

Sprint Planning

Create sprints, assign tasks, track timelines, and manage the backlog in one unified planning view with capacity context baked in from the start.

Overdue Alerts

Automated daily digests and in-app alerts notify leads and assignees before overdue tasks cascade into blocked sprints and missed milestones.

Questions & answers

Everything you need to know about Workload Distribution

Common questions from engineering leads, scrum masters, and PMs evaluating TARO's capacity management.

TARO builds a capacity score for each member from four signals: active task count in the current sprint, estimated effort per task, deadline proximity of the soonest tasks, and historical completion velocity how many tasks they typically complete per day over the last 30 days. Someone with 12 tasks and a 6-task-per-sprint average is flagged overloaded; someone with 4 tasks and 10-task capacity is flagged available. The overloaded threshold is configurable by workspace admins.
TARO matches tasks to available members using three criteria in priority order: skill and ownership match (has this person worked on this part of the product or codebase?), current availability (how much capacity do they have now?), and deadline alignment (can they realistically finish before it's due?). If several match equally on skill and availability, TARO picks the one with the highest remaining capacity. The suggestion always shows its reasoning, so leads can evaluate it in context.
No nothing moves without your approval. TARO surfaces suggestions and waits for a human decision. Accept all in one click, accept individual ones, or dismiss the set. This is intentional: workload decisions involve context TARO doesn't always have team dynamics, upcoming leave, undocumented priorities. TARO brings the data; the lead makes the call. You can accept all in one click after reviewing, but the click is always yours.
In real time, every time a task is created, completed, moved, or reassigned anywhere in the sprint. No scheduled refresh, batch calculation, or manual sync. If a developer completes three tasks at 11am, the view reflects it by 11:01am. This matters because overload can develop suddenly a new bug logged on day 4 can tip someone from 78% to 96%. TARO catches it immediately, not at the next daily standup.
Dismiss it in one click, no reason required. To help TARO learn, add a short note (e.g. Marcus is the only one who understands this part of the codebase). TARO uses dismissals and overrides as training signal to improve future suggestions for your team. Teams that override regularly find that after 2–3 sprints, the suggestions align much more closely with how their team actually works.
Yes. If a member is assigned tasks across multiple active projects and sprints, TARO aggregates their total load across all projects when calculating capacity. Someone who looks free in Project A but is deeply committed in Project B shows their real availability, not a misleadingly low number from a single view. Workspace admins can configure whether cross-project capacity is tracked at the individual, team, or workspace level.
Taro · AI project management

Taro plans, tracks, and flags risks before they hit.

Keep every project on track with AI that spots slippage early and tells your team what to do next.

Start free with TaroBook a demo
87%
on-time delivery
2.4x
team throughput
0
deadlines missed
35%
fewer status meetings
Worksbuddy© 2026 Worksbuddy