Case Study: Achēv achieves stronger language assessment fraud detection with Adastra and Amazon Rekognition

Achēv anticipates serving 20,000 clients annually with Adastra

Achēv, a not-for-profit organization supporting newcomers to Canada, sought to develop an AI-based alternative for manual fraud detection in their language assessments. Their goal was to ensure the integrity of these tests by preventing malpractice. To overcome this challenge, Achēv partnered with vendor Adastra.

Adastra implemented a solution leveraging Amazon Rekognition to identify fraudulent activities like unauthorized individuals present, screen switching, and off-screen referencing. This robust fraud detection ensures assessment integrity and has enabled Achēv to anticipate serving 20,000 clients annually. The solution also allows for the simultaneous assessment of multiple clients, significantly enhancing their operational efficiency and service reach.

Achēv