Artificial intelligence with clinical

impact

WHAT WE DO

Use cases

We create innovative solutions for biomedical research and diagnostics.

We help achieve universal healthcare for all, bringing AI to diseases that are not yet in the digital world.
WHAT WE DO

Developing AI algorithms for medical image analysis.

Our AI factory creates and validates high-quality AI models for image analysis with a fast and standardized protocol.

We help you create your algorithms based on your data or new images acquired with our devices. These AI models can be deployed on our web platform, smartphones (edge-AI), or your infrastructure.

Design

We transform clinical needs into digital solutions based on mobile technology and Edge-AI.

Build

We build robust and reliable artificial intelligence following STARD-AI principles and international guidelines such as CONSORT-AI and SPIRIT-AI..

Deploy

We deploy and integrate AI models on smartphones, web platforms or in real clinical environments.

Learn more
How we do it
remote diagnosis

Transforming clinical needs into innovative solutions

data security

Under GDPR compliance, ISO 13485 and IVD Directive

custom system

Data quality and AI traceability

access from any device

Smartphones as enablers of digitisation

send samples

Integration into clinical routines

send samples

AI deployment on smartphone or in the cloud

work with us

Develop your career at SpotLab

We are looking for talent and experience with the desire to change the world.

They trust us

Sello de excelencia de la UE - Horizonte 2020
Logo CDTI - Spotlab
Comunidad de Madrid - Consejería de economía, empleo y hacienda - Spotlab
eit Health - SpotLab
Estrategia de emprendimiento y empleo joven - Garantía juvenil
UE - Fondo Europeo de Desarrollo Regional - Spotlab
Gobierno de España - Ministerio de Economía - Spotlab
red.es - Spotlab
PYME Innovadora - Spotlab
This project has received funding from the European Union's Horizon 2020 - Spotlab
Logo Ashoka - Spotlab
Logo de la Universidad Politécnica de Madrid - Spotlab

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 881062