AI Factory Portfolio
Our AI factory creates and validates high quality AI models for image analysis with a fast and standardized protocol. We help you to create your algorithm based either on your own data or new images acquired with our devices.
Full solutions can be deployed in our easy-to use web and smartphones (edge-AI) or you can deploy the AI models in your own infrastructure.

Differential cell count in bone marrow aspirates
Hematology
AI model to support differential cell count in bone marrow aspirate samples developed in collaboration with Hospital 12 de Octubre (Spain).

Detection and quantification of filariae
Parasitology
Classification of 4 filarial species (Loa loa, Brugia malayi, Wuchereria bancrofti, Mansonella perstans) in human blood samples with an AI model developed in collaboration with Instituto de Salud Carlos III (Spain).
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Detection and quantification of geohelminths
Neglected Tropical Diseases
AI model for identification and quantification of helminth eggs (Trichuris trichiura, Ascaris lumbricoides and hookworm) in stool samples in collaboration with Kenya Medical Research Institute (Kenya).

Detection of malaria parasites
Infectious diseases
AI model for the detection and quantification of malaria parasites in blood samples at the Instituto de Salud Carlos III (Spain).
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Chagas disease
Neglected Tropical Diseases
AI model for detection of Trypanosoma cruzi parasites in blood samples with the Universidad Mayor de San Simón (Bolivia) and the Instituto de Salud Carlos III (Spain).
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Quantification of Leishmania parasites
Microbiology
Detection and quantification of parasites of cutaneous leishmaniasis in blood in collaboration with the Universidad Mayor de San Simón (Bolivia).
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Quantification of filariae
Parasitology
Automatic detection and quantification of microfilariae in blood samples at the Instituto de Salud Carlos III (Spain).

Quantification and subtyping of lung lesions
COVID19
Identification, quantification and characterization of different COVID-19 lesion patterns in chest CT images.

RDT Universal reader
Several diseases
Algorithm capable of interpreting the result of any rapid test up to 3 bands. It has been tested in several pathologies including: COVID-19, Chagas and Cryptococcosis.

Quantification of Cryptococcus
Micology
Quantitative reading of a qualitative LFA for the detection of cryptococcal antigen. This algorithm correlates band intensity with antigen concentration.

Semicuantitative reading of cryptococcus antigen test
Micology
This algorithm automates and standardizes the reading of a semiquantitative cryptococcosis LFA by correlating the intensity of its bands.
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Automatic reading of COVID-19 rapid tests
COVID-19
OVID-10 antigen and
AI model capable of reading COVID-19 antigen and antibody rapid tests.
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