5 Things You Didn’t Know You Could Use Our Software For

Most people think of our software as a tool for analyzing traffic behavior and improving safety. But once it is deployed in the real world, users often discover applications that go far beyond the original purpose.

1. Ground Truth for Sensor Validation

When new sensors are produced, manufacturers need to verify that they detect objects correctly and consistently. Even small defects in a lens or sensor component can affect detection performance. Because our software produces highly consistent and repeatable detections, it can be used as a reliable reference. Some teams compare their sensor output against our system to verify whether the hardware is detecting pedestrians correctly. In other words, our software can act as a ground truth layer for validating sensor performance.

2. Quality Control in Hardware Production

Sensor manufacturers often test equipment during production to make sure each unit performs as expected. Instead of relying only on internal test signals, manufacturers can run real world detection checks. By comparing sensor detections with what our system observes, they can quickly identify units that behave differently from the expected baseline. This makes it possible to catch subtle hardware defects earlier in the production process.

3. Training Data Validation for AI Systems

Training AI models requires large amounts of labeled data. But high quality labels are critical.

Our software can help verify whether training data reflects real world behavior correctly by providing auto-labeled data. If another model is trained to detect pedestrians, cyclists, or vehicles, its output can be compared against our detections to evaluate accuracy and consistency. This helps teams validate both their datasets and their models.

4. Benchmarking Detection Performance

Different sensors and perception systems often claim high detection accuracy. But comparing them objectively can be difficult. By using a consistent reference system, engineers can benchmark how well different sensors perform under the same conditions. This makes it easier to evaluate improvements in hardware, firmware, or detection algorithms.

5. Testing System Stability Over Time

Perception systems can degrade over time due to environmental factors, calibration drift, or hardware wear. Running periodic comparisons against a stable reference system allows operators to monitor whether detection quality changes over months or years. This provides an early warning if sensors begin to behave differently.