Biometric Vision Facial Recognition API vs. Oz Biometry
A side-by-side comparison based on G2 review data.
| Metric | Biometric Vision Facial Recognition API | Oz Biometry |
|---|---|---|
| Overall rating | 4.3 | 4.7 |
| Review count | 12 | 16 |
| Ease of use | 8.8 | 9.8 |
| Ease of setup | 7.1 | 9.0 |
| Quality of support | 8.4 | 9.8 |
| Meets requirements | 9.4 | 9.6 |
| NPS | 50 | 68.75 |
| Small Business | 58.3% | 50.0% |
| Mid-Market | 25.0% | 37.5% |
| Enterprise | 16.7% | 12.5% |
| Total page views | 68 | 55 |
| Total LLM citations | 120 | 34 |
Biometric Vision Facial Recognition API
A Facial Recognition API with superior accuracy and privacy built-in at the core. This API allows you to verify two images are the same person (one-to-one or face verification) or identify a person from a database of images (one-to-many or face identification). Here’s a highlight of some of Biometric Vision’s best features so far: - Anonymizing images into an alphanumeric string (binary) that cannot be reversed engineered - 99.99% accuracy in the most challenging scenarios - Uses up to 180 landmarks to create a face template - Blistering speed with a face match time of 130ms -
Oz Biometry
Oz Biometry - Biometric face recognition with the highest accuracy: 99.99% in NIST FRVT. Developed by Oz Forensics specialists, the biometric module incorporates the latest practices in artificial intelligence and is consistently improved by continuous data enrichment. Face recognition algorithm from Oz Forensics achieved one of the best test results in accuracy on LFW dataset in University of Massachusetts tests in 2020 MIT LFW. The Oz Biometry module allows to identify people with a speed of less than 1 second and with 99.87% accuracy (according to MIT LFW tests).