Noul – AI-Powered Diagnostics for Blood and Cancer
Noul is an AI-driven diagnostics company committed to transforming malaria, hematology, blood morphology, and cervical cancer testing through automation and digital innovation. Our miLab™ platform integrates staining, imaging, and AI-powered analysis into a compact system that delivers fast, reliable, and standardized diagnostics across diverse clinical environments. By digitalizing workflows for malaria detection, CBC testing, morphological assessment, and cervical cytology, miLab ™ enhances accuracy and accessibility while reducing the burden of manual procedures. Noul’s mission is to expand equitable access to high-quality diagnostics and improve health outcomes worldwide through innovative, technology-driven solutions.
miLab™ – AI Powered Compact, automated platform for hematology and cytology diagnostics.
●miLab™ Platform = An all-in-one system that fully automates microscopic diagnostics from sample preparation to AI-driven analysis.
●miLab™ Cartridge = A smart, scalable cartridge adaptable to a wide range of blood and cytology diagnostics.
miLab™ Analysis Software (miLab ™ Viewer) = A web-based viewer enabling real-time review of result produced by AI-powered analysis
Product Introduction
miLab ™ MAL – AI-assisted Malaria Microscopy
miLab ™ MAL automates blood smear imaging and AI-driven parasite detection, delivering accurate and standardized malaria diagnostics. Designed for resource-limited or high-burden settings, the system improves speed, reproducibility, and accessibility.
miLab ™ BCM – AI Powered Digital Hematology for CBC & Morphology
miLab ™ BCM integrates CBC testing with AI-powered digital morphology to streamline hematology workflows. The system identifies and classifies abnormal cells, supports rapid screening, and enhances decision-making with high-resolution digital imaging—all within a compact automated platform
miLab ™ CER – AI -based Digital Cytology for cervical screening
miLab ™ CER automates Pap staining, imaging, and AI-based assessment, reducing more than 20 manual steps into a simplified, standardized workflow. High-quality digital images and consistent interpretation support improved cervical cancer screening and laboratory efficiency.