Medsi AI's Platform Approved as Class II Medical Device in Mexico

May 29, 2025
Medsi AI's platform has been approved as the first Class II Software as a Medical Device (SaMD) for preventive health in the Western Hemisphere, according to a press release. This approval by COFEPRIS allows smartphones to be used as medical diagnostic tools.

Medsi AI has announced that its digital health platform has been approved as the first Class II Software as a Medical Device (SaMD) for preventive health in the Western Hemisphere. This approval by COFEPRIS, Mexico's equivalent of the FDA, enables smartphones to function as sophisticated medical diagnostic tools, .

The platform allows users to conduct a 70-second 'video selfie' using any device with a camera, such as a smartphone, to measure over 20 vital signs and biomarkers, including heart rate, blood pressure, and oxygen saturation. This innovation aims to make preventive healthcare more accessible to millions of Mexicans.

Backed by strategic investor Laboratorios Sanfer, Medsi AI has secured USD $3 million in Seed 1 funding to accelerate its mission of transforming healthcare in Mexico. The platform is designed to detect early signs of chronic conditions like diabetes and hypertension, allowing for timely intervention.

Medsi AI is collaborating with government agencies, healthcare providers, and corporations to integrate its technology into existing healthcare systems, aiming to improve public health outcomes across Mexico.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Healthcare & Life Sciences AI AI Brief AI Brief (X)
Free newsletter

Life AI Weekly

Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.