Delivery Predictability

More output shouldn't mean less predictability

AI speeds up writing code, but it doesn't make delivery more reliable. LinearB tracks planning accuracy, flags at-risk work and forecasts delivery dates from your own history, so you can course-correct before deadlines slip.

Trusted by the teams transforming software delivery

What your software factory is doing to your engineers

AI shifted engineers from writing code to reviewing it. Learn to read the strain signals in your own engineering data - before they show up as attrition.

Planning Accuracy

See exactly how reliably your team hits its commitments

Track planning accuracy and capacity accuracy across every sprint and team. Understand where and why commitments slip, and use that data to forecast with confidence and set expectations your stakeholders can count on.

Work in Progress

Know which commitments are at risk before it's too late

LinearB tracks cycle time, pickup time, and PR age across every team in real time. When work starts to drift, you see it early enough to act not after the sprint is already lost.

Project Forecasting

Know your delivery date with a probability, not a guess

Project Forecasting runs Monte Carlo simulations on your own delivery history to show the odds of finishing by any date. Insights flag stalled issues and overloaded developers, so you can act before the date slips or rescope early.

Prior to LinearB adoption, we had challenges with feature delivery predictability. Knowing when a release will hit, gauging the timeframes, and planning accuracy are all crucial to us. With LinearB, our releases have become more like clockwork, with surprises (the undesirable ones, at least) becoming a thing of the past.

Marko T.

Engineering Chief of Staff, Assignar

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Report

See it on your data

Get a live look at how reliably your teams hit their commitments.

Your planning accuracy by team and sprint

Which commitments are at risk right now

A delivery forecast for your next release