riteVision is a cloud-based SaaS solution, using a neural-based network with machine learning algorithms to replace antiquated OCR and vehicle recognition systems.
In most cases throughout the North American toll industry, OCR features low auto-pass rates, which implies higher costs for manual image review in order to process large volumes of non-automatically processed license plates and improvable reliability features, implying higher volumes of calls at Customer Service Centers to sort our wrongful records.
riteVision can replace traditional OCR and license plate recognition systems, allowing for a substantial increase in automated image review. As a result, organizations will see cost-savings almost immediately, as the need for manual review decreases.
Some key benefits, specifically tailored for the transportation industry, include the following:
- 99.9% accuracy rates; greater accuracy than OCR
- 50% less manual review times, resulting in total reduced cost
- Increases in availability, response, and accuracy performance standards
- 18% increase in auto-pass
- High availability and scalability
- Continuous tuning from self-learning
- Easy integration
- No upfront costs
- Low fixed price per image set
Centered around machine learning algorithms, riteVision is the image review of the future.
riteVision allows for greater accuracy and automation and can reduce manual review by 50%.
Machine learning system has an 18% higher throughput and a 0.06% lower error rate.
- These numbers are functional numbers meaning without exceptions for human readable, fuzzy, obstructed, etc.
≥ 99.5% Accuracy to Exceed RFP Requirements
- Accurately determine OCR values for plates legally mounted and unobstructed
In addition to providing higher throughput with fewer errors, the machine learning system provides other classifications
- Motorcycle, emergency vehicle, obstructed plate, etc.