L2M Launch / Qc Fall 2025 / Autonomous lawn care for precise, sustainable upkeep with minimal labor on large or restricted lands

EdgeStar AI is building an all-in-one autonomous lawn care robot designed to handle every major task needed to maintain large residential and commercial lawns. Unlike current robotic mowers that only cut grass, our robot can mow, weed, edge, and manage the full lawn maintenance process without any human involvement. It is fully electric, uses AI […]

Read More
L2M Launch / Qc Fall 2025 / Empowering Social Workers Through Smart Technology

A survey conducted in 2024 revealed that up to 16% of Quebec’s social workers are considering leaving their profession due to cumbersome administrative tasks and intense workloads. Many of the social workers must conduct home visits as part of their job which sometimes can be challenging and risky, especially when dealing with abuse, addiction, homelessness […]

Read More
TRLUP – Apex Health Digital Health Platform enabling global health record accessibility

Apex Health is an emerging Canadian digital health company dedicated to advancing equity, security, and innovation in health information management and informatics. Its operations are focused on delivering privacy-first digital health solutions, including health data analysis using machine learning and predictive analytics. Apex Health is committed to helping Canadian healthcare organizations optimize clinical outcomes, enhance […]

Read More
TRLUP – Quinan Labs, Agentic AI Technology

This project is focused to democratize enterprise-level information technology solutions for Atlantic Canadian small and medium sized businesses (SMBs) through a revolutionary one-person or small team, agile, artificial intelligence (AI)-powered consultancy model. This project will provide key innovation using cutting-edge AI tools (Claude, agentic AI), which can deliver digital transformations at 1/10th the traditional cost […]

Read More
L2M Validation / Qc Automne 2025 / Développement d’un Scribe Intelligent pour la Préconsultation Médicale

Le projet vise à développer un système d’intelligence artificielle capable de remplacer le rôle traditionnel du scribe en clinique. Actuellement, dans certaines cliniques à Montréal, les médecins se sont regroupés pour créer des formulaires comprenant des questions essentielles à poser à un patient se présentant avec certains symptômes. Par exemple, dans le cas d’un mal […]

Read More
TRLUP – NovaAI Solutions

NovaAI Solutions will offer a suite of secure and customizable AI services designed for local businesses, including inventory forecasting using sales patterns and seasonal data, email categorization to help businesses prioritize important messages, automated reporting and business analytics summaries, offer admin task automation and document processing, and review and feedback analysis for actionable insights. The […]

Read More
Recurrence analysis of neuronal behaviors and networks

The goal of this project is to bridge the fields of neuroscience and nonlinear dynamics by leveraging advanced machine learning algorithms to analyze recurrence patterns in neural wave data. Specifically, the project focuses on studying traveling cortical waves – a fundamental phenomenon in brain activity – using recurrence quantification analysis enhanced by machine learning techniques. […]

Read More
TRLUP-NeuroScope – wearable, AI-integrated, portable EEG device

Current EEG (electroencephalogram) systems used in clinical and diagnostic settings are often bulky, expensive, and require patients to remain in a controlled environment for extended periods. This limits their accessibility and practicality, especially for patients suffering from neurological conditions such as epilepsy who require continuous, long-term brain monitoring to detect abnormal brain activity and predict […]

Read More
TRLUP Allergen Detection App

For many Canadians with food allergies, knowing what is in their food is important. This project helps by creating an allergen detection app that can process a picture of a product’s ingredient list from the package and then checks for known allergens. The impact of this project is helping tens if not hundreds of thousands […]

Read More
Développement d’un système d’intégration et d’augmentation des données pour la détection des fractures atypiques et complexes en utilisant des infrastructures de calcul avancées

Ce projet vise à développer un système intelligent pour aider les médecins à détecter et segmenter avec précision les fractures osseuses atypiques et complexes à partir d’images médicales comme le scanner (CT) ou l’IRM. Ces types de fractures sont particulièrement difficiles à identifier avec les méthodes traditionnelles en raison de leur rareté, de leur diversité […]

Read More