Know when each part runs out, on your bike, from your riding

• A wear rate built from your rides

  Climbing, power, descending, weather, and volume each carry a factor. The list is sorted by effect, so the thing driving wear on your bike is at the top.

• The headline figure is the strongest signal

  When the model knows more than the manufacturer rating, the prediction leads. The measure behind the figure is always named: Distance, Duration, Time, or Predictive.

• Web and phone agree

  The same prediction, the same confidence, the same factors on componentry.app and in the app. There is one model, not two.

Good to know. Predictions are marked purple everywhere they appear so a modelled figure is never mistaken for a measured one. Confidence and the model version are shown on every prediction.

• Distance remaining and the date it lands

  Each component shows what is left and when, at your rate, it runs out.

• Cards lead with the answer

  Prediction cards open collapsed on the figure. Expand one for the provenance: what was measured, what was assumed, and how confident the model is.

• Refuses false precision

  Sub-watt figures collapse to under one watt and far-off dates round to years. Naming what is not known is part of the model.

Good to know. Dates appear when they fall within two years. Beyond that Componentry shows 2+ years instead of inventing precision it does not have.

• Loss and recoverable, side by side

  The band on your bike card shows the total and the share you can get back with a clean and lube. The gap between them is stretch, which only a replacement removes.

• Wax-aware

  Mark a chain as waxed in a service note or check and the model treats it accordingly. Waxed or lubricated shows on the component list.

• Sharpened by your service records

  A lubrication reminder and your chain stretch readings feed the model, so the estimate tightens as you record what you do.

Good to know. Works with a connected bike computer, and with Strava-only rides at reduced accuracy. Sub-watt figures read as under one watt. The chip disappears when there is nothing to recover.

• Training-plan presets

  Normal, Build, 2-week taper, and 4-week taper change how much riding the model expects between now and the day.

• Per-component readiness

  Each part gets its own projection on the date, so a chain that is fine and a set of pads that is not are not averaged into one number.

• Per-profile forecasting

  Race wheels and training wheels wear differently. Pick the profile you will ride and the forecast follows it.

Good to know. Race-day readiness is profile-aware: forecast a specific setup, all of them, or components with no profile. Every readiness card lists what it assumed.

• Progress you can see

  A meter on the dashboard counts the rides toward the next tier and says what it unlocks.

• Bike computer data goes deeper

  Power, cadence, and terrain from ride files sharpen wear rates and chain power loss beyond what a ride summary can.

• Strava power counts too

  When a head-unit ride is paired with its Strava copy, the Strava power feeds the chain model.

Good to know. Basic predictions work from synced rides. Advanced insights use ride files from a connected Garmin, Wahoo, or Hammerhead computer, or .FIT uploads.