tAIre Forge
An AI-based engineering platform that predicts key tyre behaviours directly from specification data.
Turn specification and experimental data into reusable predictive engineering intelligence, evaluated across different pressure and load conditions before physical testing.
Performance is often confirmed only after physical prototyping
Tyre performance characteristics are typically evaluated only once physical prototypes are available, extending development timelines and limiting how many design variants can be compared early in the process.
How it works
- 01
Import specification matrix and target load and pressure conditions
- 02
Run predictive models for inflated profile, footprint, rolling resistance and cornering stiffness
- 03
Compare predicted performance across pressure and load sweeps
- 04
Export results for design review and validation planning
- Specification matrix
- Inflation pressure range
- Vertical load range
- Load cases
- Predicted inflated profile
- Footprint geometry
- Rolling resistance estimate
- Cornering stiffness estimate
Configurability, integration and deployment
Matched to your specification format
A dedicated connector translates a customer's specification matrix into Moonar's proprietary format, so predictions are generated directly from existing engineering data.
Structured outputs for design review
Performance predictions are exported in structured formats for use in design review, reporting and comparison against existing validation data.
Cloud or on-premise
Runs in a customer-managed cloud environment or on-premise infrastructure, with role-based access and security requirements adapted to internal IT policy.
Capture, design and predict within one connected platform
Discuss tAIre Forge with Moonar's engineering team
Talk to our engineering team about your specification format, target load and pressure conditions and how predictions should fit into your validation process.
Request a Demo