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DeepAffex is NuraLogix’s cloud-based physiological health assessment platform. It uses Transdermal Optical Imaging™ to extract facial blood-flow data from selfie videos, then DeepAffex Cloud applies signal processing and AI models to estimate metrics such as heart rate, stress, blood pressure, and other health/physiological indicators. The company explicitly positions it as for investigation use only or general wellness, meaning its intended use does not extend to medical diagnosis.
For developers, DeepAffex provides the Anura Core SDK, Web Measurement Service, Cloud API, Points Reference, Dashboard, download center, and support portal. Mobile apps can integrate via the SDK, while web applications can use WMS to run a 30-second facial health scan. The cloud API supports synchronous REST calls and asynchronous WebSocket communication, with access to cloud microservices, organization account data, and results. For companies looking to quickly embed remote health measurement capabilities, the productized integration stack is fairly complete.
On privacy, the company states that blood-flow information is encrypted before being sent to the cloud and that no facial recognition is performed. When using Anura, facial images or video recordings are not stored, and the images/recordings do not leave the device. The cloud runs on a distributed cluster and can, in most cases, meet regional data storage and processing requirements. The limitations are also clear: measurements can be affected by lighting, optical quality, signal-to-noise ratio, glasses, heavy makeup, hats, facial hair, and other obstructions. Even a high-rated image may still fail if the blood-flow signal is insufficient. Some metrics recommend collecting user profile information and medical-history questionnaires to improve accuracy, which introduces additional consent and compliance work.
The main materials do not disclose a free tier, trial, or pricing. The terms only state that services may be chargeable and that fees will be notified separately, while WMS access also requires contacting the company. This makes it look more like an enterprise sales model. It is suitable for development teams working on insurance, corporate wellness, remote health management, health apps, research, or non-medical health assessment use cases. It is not suitable for products that require medical diagnosis, prescription decisions, or use by minors.
The website does not provide information on mainland China access, a Chinese interface, local payment methods, or local compliance deployment, so china_access can only be rated as unknown. If used for business in China, key issues to verify include network connectivity, cross-border data transfer, regional deployment, payment contracts, and authorization for sensitive personal information. Alternative approaches include using health data from wearable devices, domestic remote vital-signs SDKs, or Anura Lite for proof-of-concept validation.
⚠ This review is compiled from public sources and does not constitute a purchase recommendation. Verify all facts on the vendor's official site. Verify on deepaffex.ai official site.
deepaffex.ai is an Canada AI Apps provider. TG4G tracks its product information, an overall rating of 8.0/10, and a China-accessibility score of Workable. Click "Visit Official Site" to reach deepaffex.ai directly.