Know Your

Know Your Project Completion Date
Before the Deadline Arrives

TARO predicts your real completion date from team velocity, blockers, and sprint history, with variance and confidence.

See Your Prediction See how it works

How it works

From project state to accurate prediction in four steps

TARO reads what your team is actually doing not what was planned and predicts the finish date that reflects reality.

Velocity

TARO measures how fast your team actually moves

First, TARO reads your team's real throughput tasks completed per sprint over the last 30, 60, and 90 days, broken down by member and complexity. This baseline replaces the optimistic estimates that make deadlines wrong.

Blockers

Known blockers and sprint history factored in

Velocity isn't the full story. TARO also reads three signals history can't capture: tasks marked blocked, unresolved dependencies, and how many new tasks get added mid-sprint. Every risk that could push the date is counted.

Prediction

Three numbers that tell you everything you need to know

TARO combines velocity, blockers, scope history, and sprint pattern into a single prediction with three actionable outputs. Not a Gantt chart, not a 40-slide forecast deck three numbers you can act on before committing to a stakeholder date.

Variance

The variance is the signal. Not the headline.

An 8 day variance found in week 2 of a 6 week project is recoverable; the same variance the day before launch is not. TARO surfaces it the moment it's visible, with runway to cut scope, unblock tasks, or reset expectations before a crisis.

Early enough to act
Scope levers visible
Stakeholder reset signal
AI score applied
Live table update

Why Completion Analysis

Six reasons teams never go back

Every team has shipped a project late that looked on track two weeks before the deadline. Completion Analysis exists to make that stop.

Predicted date based on what's actually happening

Not the date set at planning, or the one your most optimistic team member believes the date your current velocity, blockers, and sprint history say will actually happen.

Variance visible before it becomes a crisis

An 8 day slip found in week 2 is a planning adjustment; the same slip found the day before delivery is a crisis. TARO shows the gap while there's still time to close it.

Confidence level tells you how much to trust it

A prediction from 2 sprints deserves less trust than one from 12. TARO tells you exactly how confident the model is, so you know whether to act now or keep monitoring.

Blockers counted, not ignored

Most predictions ignore blocked tasks because they can't estimate the delay. TARO counts them, weights them by deadline proximity, and factors them into the completion date.

Sprint history beats sprint planning optimism

Sprint planning is optimistic; sprint history is honest. TARO uses what your team has actually delivered, not what they promised, as the baseline for every prediction.

Stakeholder conversations before the missed deadline

When TARO shows an 8 day variance in week 2, you reach stakeholders with a revised date, a plan, and credibility intact. Discover it on launch day and none of that is left.

Who uses it

800+ product teams

already using TARO

Built for every team that commits to a deadline

Engineering leads, PMs, scrum masters, and founders use Completion Analysis at different stages, but for the same reason. The committed date and the real date need to match, and TARO keeps them aligned before the gap shows.

87%

Prediction accuracy

3×

Earlier variance detection

+2d

Average prediction error

73%

Fewer deadline surprises

Engineering Leads

Are we on track? stops being a feeling and becomes a number.

Before enrichment, a sales rep spends the first 5 minutes of a discovery call asking basics. With Lio, the rep arrives knowing the prospect's role, company size, tech stack, and more.

Completion analysis is just the start

TARO's intelligence runs across the full project lifecycle from the moment a task is created to the day the sprint closes.

Workload Distribution

TARO analyses team capacity and suggests exact reassignments to balance overloaded members before a deadline slips with one click to apply.

Risk Analytics

Tracks overdue tasks, stalled dependencies, and sprint velocity trends, surfacing which tasks are most likely to slip before they do.

Sprint Planning

Create sprints, assign tasks, and track timelines in one unified view with TARO's velocity data baked into the capacity estimates from the start.

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.

Questions & answers

Everything you need to know about Completion Analysis

Common questions from engineering leads, PMs, and founders evaluating TARO's prediction model.

TARO builds the prediction from three layers. First, team velocity the average tasks per sprint over the last 30, 60, and 90 days, weighted toward recent sprints. Second, known blockers and dependencies each adds delay proportional to how deadline-critical it is and how long blockers stay open. Third, sprint history if this team adds 4–6 tasks mid-sprint, that creep is built in. The three signals combine into one finish date.

Confidence reflects how much historical data the prediction rests on and how consistent it is. A team with 10 completed sprints, stable velocity, and predictable scope generates 85–95% confidence. A team with 2 completed sprints, high velocity variance, or frequent mid-sprint changes generates 55–70%. The level is honest about its own uncertainty a 60% prediction is a directional signal, not a commitment. Higher confidence predictions set stakeholder expectations with much more certainty.

TARO reads every task marked blocked and applies a delay estimate from two signals: how long blockers historically stay open for this team (resolve them in 2 days and a current blocker adds roughly 2 days), and how deadline-critical the blocked task is (one on the critical path adds more delay than a parallel one). External dependencies are weighted more heavily, because TARO sees they stay open longer than internal blockers do.

TARO predicts from the very first sprint, but confidence improves with history. With 1–2 sprints, expect 55–65%, useful directionally but not for external commitments. With 4–6 sprints, confidence typically reaches 75–85%. With 8+ sprints, most teams see 85–92%. The model also improves as it learns team-specific patterns: how you handle scope creep, how long blockers stay open, whether velocity is stable.

Yes the prediction recalculates every time the project state changes. Complete a task and the velocity baseline updates; log a new blocker and the delay estimate adjusts; add tasks mid-sprint and the scope creep factor incorporates the new data. The predicted date, variance, and confidence always reflect the current state, not a snapshot from Monday's planning. Teams typically check Completion Analysis at the start of each sprint week to see how the prediction has moved since the last reading.

Every wrong prediction is a learning opportunity. TARO tracks each prediction against the actual delivery date and feeds the variance back in, so teams with consistent errors (always 3 days off) see the model self-correct over time. You can also flag unusual sprints as anomalies (half the team on leave) so TARO excludes them from the baseline. The goal isn't first-try perfection it's an honest, improving estimate that beats no prediction at all.

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