Independent Vendor Tests

continue to prove the premier accuracy and speed of our face matching algorithm

Cognitec Systems regularly participates in renowned vendor tests for independent performance validation.

FRVT 1:N Identification (2019)

Cognitec announced its successful participation in the NIST FRVT 1:N Identification, confirming the solid market position of the company’s matching technology, and the achievements of focused algorithm research and development. The September 2019 results, comparing 203 algorithms from 51 commercial developers and one university, show Cognitec’s high performance in accuracy tests for large galleries of frontal mugshots and of unconstrained images (Wild).

FRVT 1:1 Verification (2019)

Cognitec reported remarkable leaderboard positions in the FRVT 1:1 Verification in 2019, ahead of all face recognition companies with established market presence and products. The November 2018 results, comparing 100 algorithms from 57 developers, show Cognitec’s high performance for accuracy tests with visa photos. In addition, Cognitec’s template generation was the fastest among the highest ranking algorithms with false non-match rates lower than 0.01, at a false match rate of 0.0001.

FRVT Age Estimation (2013)

Test results on the performance of age estimation algorithms confirmed Cognitec’s leading position in the face recognition market. The company's algorithm performed with the highest accuracy for all age groups. Most notably, it showed superior performance “in the youth and senior age groups, leading the next most accurate algorithm in 5-year accuracy by 30% and 16%, respectively,” according to the report.


FRVT results do not constitute endorsement of any particular system by the U.S. Government. Download complete test results at

Use of proprietary databases

Cognitec’s algorithms are not optimized or trained on databases used for tests. Training and optimization are performed on internal proprietary databases which do not contain data from test databases. Consequently, Cognitec’s test results can be generalized to similar unknown sets of data.