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© 2026 SIG Machine Learning Pty Ltd (ACN 637 894 690). All rights reserved.

Nexgineer™ and SwitchPad™ are trademarks of SIG Machine Learning.

SwitchPad is an independent technology developed by SIG Machine Learning and is not affiliated with, endorsed by or sponsored by Formula One World Championship Limited, Formula One Licensing B.V., the FIA or any Formula One team unless expressly stated otherwise. F1, FORMULA 1, FORMULA ONE, FIA FORMULA ONE WORLD CHAMPIONSHIP, GRAND PRIX and related marks are trade marks of their respective owners.

Street circuit at dusk
SwitchPad™SwitchPad™Platform & SDK

Race tactics software.

Every tactical option. Lap by lap.

See it run
  • Optimum planning
  • Race tactics
  • Platform, API and Python SDK

Optimum plan

Lap 30 of 72

NowP1P2P3P4P5P6P7P8110203040506072

Our car, P6: pit lap 44 for softs. Projected P4.

SoftMediumHardProjected

Attack · Undercut

Lap 30
Target
P4 car
Window
Lap 35
Gap
3.0 s
Options compared at lap 30
OptionPit lapTyreRank
No actionNo stop–6
Undercut35S5
UndercutResolvedClears the rival at the flag
See it run

Race simulation

The optimum plan for every driver, re-run each lap.

Decision analysis

Every tactical option, weighed against that plan and the rivals around you.

Pre-Race

Configure the questions before you need the answers.

Race, tyres and pace, racing and tactics, set up step by step. Race day starts ready.

  • Validated inputs
  • Your team models
  • Assumptions on record

Pre-Race

Configuration status

  1. 1 · Race
  2. 2 · Tyres and pace
  3. 3 · Racing
  4. 4 · Tactics
  5. 5 · Simulate
  6. 6 · Ready
  • SetupValidated
  • RulesEstimated
  • Tyre inventory2 to confirm
  • Starting gridConfirmed

Every input shows where it came from: confirmed by your team, or estimated.

Race

From the plan to the call.

  1. Plan

    Every driver's optimum plan, re-run each lap.

  2. Tactics

    Attack, defend and respond windows, shown before they open.

  3. Options

    Select a window to see each option and where it finishes.

Tactics

Laps 31 to 50

Tactic lanes for our car, laps 31 to 50. Attack: undercut windows open on laps 35 and 44, with overcut and follow watched from lap 35 to 44. Defend: idle. Respond: safety car and VSC responses ready from lap 31 to 35.

AUndercut

AOvercut

AFollow

DPrevent undercut

DCover undercut

DCover overcut

RSafety car

RVSC

3135404450

Attack · Undercut · lap 35

Gap 3.0 s to the P4 car

No action

P6

Undercut

P5

UndercutConfidence caution-dependentProjected finish among the cars we race
Open windowWatchingIdleSelect an undercut window

Respond

Ready the moment the race changes.

A safety car or VSC can close a window in a lap. The response is already evaluated.

  • Safety car and VSC
  • Pit or stay out
  • Finish either way

Respond · VSC

Lap 55

VSC

VSC running since lap 55

Projected finish · baseline P4

  • Stay outP3
  • Pit nowP2
PitConfidence high

Post-Race

Review the race as a sequence of decisions.

Review the reasoning alongside the result, and carry it into the next race.

  • Known at the time
  • Action taken
  • What happened next

Decision review

Lap 55

  1. Known at the time

    VSC running. Pit now: projected P2. Stay out: projected P3.

  2. Action taken

    Pitted on lap 55 for softsAligned

  3. What happened next

    Finished P4

Platform and SDK

Start with the platform. Integrate as far as you need.

Run the SwitchPad app as it is, or build your own tactics system on the API and Python SDK.

App

  • Configure
  • Operate
  • Review

API

  • Connect
  • Run
  • Retrieve

Python SDK

  • Integrate
  • Automate
  • Extend
from switchpad import Client c = Client.from_env()v = c.replay.get("Zandvoort", 2026, 30, car) v.plan                       # the optimum planfor t in v.tactics("attack"):    a = v.analysis(t)    print(a.title, a.output["answer"])
  • The factory, the pit wall, or both
  • On-premise or in your cloud
  • Your data and supported team models
  • Every result traces back to its run

Series

Different series. Same scenario engine.

Five modelling groups, configured for each championship.

  • Tyre performance
  • Pit strategy
  • Pace projection
  • Overtaking and position
  • Environmental factors
  • Formula 1
  • Formula E
  • Formula 2
  • IndyCar
  • WEC
  • GT racing
  • Supercars
  • Super Formula
Show the series matrixHide the series matrix
✓ Core factor○ Secondary or situational– Minor factor
LeverF1FEF2IndyWECGTSCSF
+Tyre performanceHow tyre-related performance changes over time.
Tyre selection
Available compounds, tyre types, or tyre-set choices.
✓–✓✓✓✓✓✓
Relative offset (s/lap)
Expected pace difference between tyre options.
✓–✓✓✓✓✓✓
Performance profile
Warm-up, operating region, degradation, and end-of-life behaviour.
✓✓✓✓✓✓✓✓
Useful life
How long the tyre remains strategically effective.
✓✓✓✓✓✓✓✓
Allocation constraints
Limits on tyre availability or usage.
✓–✓✓✓✓✓✓
+Pit strategyHow stopping alters race outcome.
+Pace projectionExpected lap-time performance.
+Overtaking and positionWhether pace can be converted into track position.
+Environmental factorsGlobal conditions that influence every strategy model.

Tap a group to see its levers. Scroll across for every series.

Getting started

Three steps to race day.

  1. 1

    See it run

    30 minutes on a race replay, live or as a link.

  2. 2

    Plan it in

    Validate it on your past races, with your data.

  3. 3

    Set it up

    Connect your live feeds and run it on race day.

Why SIG ML

From decision analysis to race tactics.

SIG Machine Learning builds engineering software, powered by machine learning, used by energy operators including Santos, BHP and Origin Energy. SwitchPad is our dedicated platform for race strategy. We build the software and support your team to validate and run it.

See it run on a race replay. 30 minutes.

You'll know whether you want it for next season.

See it run