| What it does | AutoML that just works. Keep training local.
| 3D spatial perception and 4D radar-vision fusion for autonomous machines and robotics
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| Stage | MVP
| Established
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| Founded | Not given
| 2001
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| Based in | Not given
| CA
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| Pricing model | Free trial
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| Pricing | Free beta with no billing. Paid plans launching in the future; pricing not yet announced. Join the waitlist for paid plans without payment or purchase commitment.
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| Key features | - Python SDK for tuning suggestions
- Local model training with remote suggestions
- Supports classification and regression
- Included CPU demo workloads
- Efficient observation budget allocation
- Model ranking and selection
- Reference scheduler implementations
- HTTPS secure communication
| - 3D and 4D spatial perception with radar-vision fusion
- 20× faster annotation, 100× quicker ground truth generation, 4× faster training
- Support for NVIDIA Jetson, NXP processors, and embedded platforms
- Object classification, 2D/3D detection, instance and semantic segmentation
- Au-Zone Maivin vision module for object detection and segmentation
- Au-Zone Raivin 4D imaging radar with camera for challenging conditions
- Reliable perception in dust, fog, rain, and darkness
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| What makes it different | - Trains locally, not on the service—your models and data stay on your computer
- Efficient tuning using only half the observation budget of full training
- Outperforms reference schedulers in benchmarks on diverse datasets
- Free beta with no billing or account costs
| - Industry-first low-level radar-vision fusion engine
- Deploy from development to production in months instead of years
- Over 20 years of embedded engineering expertise
- Field-ready hardware modules optimized for cost, performance and reliability
- Seamless path from development to deployment with ready-to-use modules
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 29 ● no change since last check |
| Trust Flow (Majestic) | 3 | 21 |
| Citation Flow (Majestic) | 13 | 18 |
| Referring domains (Majestic) | 2 | 22 |