Innovative Projects Realized

L2M Launch / Qc Fall 2025 / Advanced MicroTesting

Le projet a pour objectif de commercialiser LOTUS-X1, un banc de test universel pour puces électroniques alliant haute performance et coût réduit. Actuellement, les chercheurs en microélectronique doivent concevoir et programmer un banc de test spécifique pour chaque puce, ce qui mobilise un temps considérable et complique la reproductibilité. LOTUS-X1 centralise tous les outils, génération et mesure de signaux analogiques, numériques et de puissance, dans une plateforme modulable, offrant ainsi aux laboratoires un dispositif réutilisable et facilement adaptable aux différents protocoles expérimentaux.

Pour réussir la transition du prototype vers le marché, deux phases clés sont prévues. La première vise à consolider un modèle d’affaires robuste : recueillir des retours clients pour affiner la proposition de valeur, élaborer des gabarits d’emails pour optimiser la relation client, définir une stratégie d’acquisition marketing et établir une structure de coûts et de revenus pertinente. La seconde phase porte sur le déploiement opérationnel : rédiger un plan produit détaillé, lancer un portail client pour recueillir suggestions et signaler les anomalies, implémenter un CRM (ex. : HubSpot) pour automatiser le suivi et élaborer une grille tarifaire cohérente.

Le succès du projet sera évalué à travers la livraison d’un Business Model Canvas complet, d’un plan produit, d’un portail fonctionnel, d’un CRM configuré et d’une tarification documentée. Le programme L2M fournira un accompagnement d’experts pour garantir la pérennité et l’efficacité de la commercialisation.

L2M Validation / Qc Automne 2025 / Validating Market Fit for a Cardiac Fibrosis-Preventing Drug

This project aims to explore the market potential of a new drug screening approach by Telescope Therapeutics that uses human stem cells to create a more accurate model for studying and testing treatments for heart scarring, known as cardiac fibrosis. By better understanding the needs and interests of potential users like pharmaceutical companies and research organizations, the project will help Telescope refine its business strategy and find the best path to bring this innovative technology to market. Ultimately, this will support the company’s goal to develop effective new therapies/drug that could improve the lives of patients with heart disease and strengthen Telescope’s position in the biotech industry.

L2M – DeepFault AI: Advanced Geoscience Software Solution

This project will validate the commercial potential of DeepFault AI, an advanced geoscience software solution that automates seismic fault interpretation using deep learning, with integrated uncertainty quantification and quality control (QC). In energy sectors such as oil and gas, geothermal, and carbon storage, reliable subsurface interpretation is essential. Traditional fault detection methods are slow, subjective, and lack mechanisms to quantify confidence.

DeepFault AI addresses these gaps by combining high-performance fault segmentation with real-time uncertainty estimation, allowing users to assess the reliability of each prediction. This is critical in high-stakes environments where interpretation errors can lead to costly drilling decisions. The system also includes a QC workflow that flags low-confidence areas, helping interpreters prioritize review.

The technical foundation is a deep neural network tailored for seismic data, using Monte Carlo Dropout, concrete dropout, and ensemble methods for uncertainty, along with patch-based training and transfer learning for broader applicability.

Through Lab2Market Validate, we aim to:

Engage industry stakeholders (e.g., oil & gas operators, CCS developers) to validate demand for uncertainty-aware interpretation;

Interview 75+ potential users to assess business viability, value proposition, and pricing;

Evaluate integration with industry tools (Petrel, OpendTect, RMS) for seamless adoption;

Validate use cases where uncertainty/QC maps guide decisions in exploration, reservoir modeling, and fault connectivity;

Assess IP, regulatory, and data management needs for on-prem or cloud deployment.

Deliverables include:

A validated business model and commercialization roadmap

Feedback from end users and early adopters

Prioritized customer segments and use cases

Demonstrated value of uncertainty/QC outputs in practice

This project supports the transition of research into scalable innovation, enabling safer, more automated, and interpretable subsurface workflows.

L2M Launch / Qc Fall 2025 / Technologies MicroMea inc.

Dans le cadre de ce projet, le stagiaire mènera des entrevues avec des entreprises agroalimentaires et d’autres organisations qui produisent de grandes quantités de déchets organiques. L’objectif est de mieux comprendre leurs besoins, leurs défis et leur intérêt pour une solution locale qui transformerait ces déchets en biogaz renouvelable, pouvant remplacer une partie du gaz naturel utilisé. Le projet permettra aussi d’identifier les obstacles à l’adoption d’une telle technologie, ainsi que les attentes des entreprises en matière d’accompagnement. En parallèle, une étude du marché et des solutions existantes sera réalisée pour estimer le potentiel de la technologie. Une attention particulière sera portée à la réglementation qui encadre la micro-méthanisation au Québec.

Anthropology, social media management, analysis and the development of strategy – Year two

This project will expand the research and development capacity of Treefrog for the creation of a social media strategy and analysis department offering unique, cutting-edge and anthropologically informed services for corporate clients.
Anthropologically informed analysis goes beyond a superficial reporting of unanalysed numerical data to provide contextualized understandings based on broader social trends and cultural practices. Using Treefrog as a case
study, I will develop a set of durable processes and services that will be refined for application for Treefrog clients, who are companies that represent well-known Canadian brands.

Etude de rémunération des auteurs en contexte évènementiel

Dans le cadre de ce projet, un étudiant à la maîtrise en lettres, spécialisé en culture et numérique, effectuera un stage à l’Association québécoise des Salons du livre (AQLS). Il aura pour mandat de recueillir et d’analyser des données sur la façon dont les auteur·rice·s sont rémunéré·e·s pour leur participation à des activités numériques organisées par les Salons du livre, comme des captations vidéo ou des diffusions en ligne. Les conditions associées à la diffusion seront également examinées. Le but de l’enquête est de mettre en place une grille tarifaire commune, adaptée aux nouvelles réalités numériques, qui servira de base pour de futures ententes entre l’AQSL et l’Union des écrivains du Québec. Ce travail aidera l’AQSL à mieux encadrer ces pratiques, à assurer une rémunération plus équitable pour les auteur·rice·s et à proposer des standards clairs à l’ensemble du secteur littéraire. Le stage permettra aussi de renforcer les liens entre l’AQSL et le milieu universitaire, tout en offrant une expérience concrète et formatrice à l’étudiant.

L2M Launch / Qc Fall 2025 / Flexible Intra-Oral Device for Continuous Salivary Biomarkers Monitoring to Diagnose Sleep Disorders

Sleep disorders like insomnia and circadian rhythm disruptions affect millions, leading to health problems such as fatigue, difficulty to concentrate, depression, various ailments including heart disease and cancer. Diagnosing these issues is challenging because current methods, such as overnight lab tests, are expensive, uncomfortable, and often unable to accurately perform real-time measurements. Wearable devices help, but mostly track movement or heart rate, missing key hormonal clues, such as melatonin levels, which are critical for pinpointing sleep disorders. There is a clinical need for a better way to monitor the individual fluctuations of hormones or biomarkers at home, without invasive lab tests. Our solution is a smart intra-oral device with a built-in biosensor that tracks melatonin levels in saliva in real-time. Because it can be wireless, will allow patients to sleep normally in the comfort of their home while collecting data. Clinicians can use this information to accurately diagnose sleep disorders and personalize treatments, like adjusting the timing of their administration and of their amount (i.e. of melatonin supplements or light therapy timing). This could reduce misdiagnoses, increase efficiency of care, and improve outcomes. We have developed a lab bench-top prototype and are currently testing its various components, which will be further miniaturized to be integrated into the device. The Lab2Market program will help us understand market needs, refine our business model towards bringing this product to the people who need it most, whether through clinics, wellness centres, or direct sales.

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 and mental health support situations.
The loss of social workers could have devastating consequences, leaving vulnerable populations without critical support and putting additional strain on healthcare, social services, and public safety. As a society, we cannot afford to lose social workers, which is why we aim to conduct research and validate our business idea by understanding the reasons behind their decision to leave the profession.
Our proposed solution is to create a mobile and web application designed to enhance the safety during home visits and increase efficiency of social workers on their daily work activities. By leveraging AI and real-time monitoring, we aim to reduce risks, improve reporting accuracy, and provide immediate support when needed.
Our platform offers proactive protection through features such as a one-tap emergency panic button (SOS), live location tracking, and pre-visit risk assessments, ensuring social workers feel secure before and during their visits. Additionally, AI-powered incident reporting, emotional state real-time detection, and automatic voice & video recording with secure cloud storage streamline documentation, will reduce administrative burdens.
Unlike traditional reporting systems, our solution integrates real-time safety measures with AI-driven insights, allowing agencies to detect patterns, allocate resources effectively, and ultimately prevent dangerous situations before they escalate.
By providing data-driven reports and a peer-support network, our application not only improves safety but also enhances overall job satisfaction, helping retain social workers in a field where burnout and high turnover are growing concerns.

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 for intelligent decision-making, and is built to handle large properties where manual maintenance is time-consuming and expensive.

The goal of this project is to further develop and refine the prototype so it’s ready for real-world deployment. Our current pilot has proven the system works, and we are now adding new features like dynamic obstacle avoidance and smart path planning. During this project, we’ll continue testing and improving the robot’s reliability, safety, and performance.

The benefit to our partner organization is early access to groundbreaking technology that will lower landscaping costs, reduce reliance on labor, and support a more sustainable, eco-friendly approach to lawn care. It will also allow them to differentiate themselves by adopting automation and clean technology early. Through this collaboration, they’ll have the chance to provide real-world feedback that shapes the final product before its full commercial launch.

In the long term, this innovation has the potential to transform how large lawns are managed across Canada and beyond, making lawn care smarter, greener, and far more efficient.

L2M – AutoSAR: Autonomous UAV Search and Rescue Using Deep Learning for Emergency Response in Remote and Infrastructure-Free Regions.

In remote and rural regions, where communication infrastructure is sparse and GPS is unreliable, emergency Search and Rescue (SAR) operations should be fast, reliable, and cost-effective. Existing technologies, such as thermal imaging and mobile-based systems like Cellular Airborne Sensor for Search and Rescue (CASSAR), depend on costly sensors, human interpretation, or the presence of a mobile device, which limits their effectiveness in many real-world scenarios. The AutoSAR solution is designed to fill this critical gap. AutoSAR is an autonomous UAV-based search and rescue system for emergency response in infrastructure-free regions. The UAV emits and receives its own signals to detect and localize individuals in distress, eliminating reliance on GPS, networks, or external sensors. By leveraging deep learning, AutoSAR estimates position and velocity from reflected signals in real time, enabling rapid, intelligent rescue missions in rural areas such as mining sites, wilderness trails, and northern communities. This technology addresses a national public safety need by offering a scalable, cost-effective, infrastructure-independent SAR solution.

Anthropology, social media management, analysis and the development of strategy

This project uses approaches from anthropology, such as corporate ethnography, to guide the development of strategies for corporate social media management and analysis. Durable strategies and processes can be leveraged by Treefrog to help build a social media management and analysis department, increasing research and development capacity and sales. Through close collaboration with the programming team at Treefrog, the results of this research will be built into a novel and comprehensive business software platform called Mergini. Mergini is a vanguard management tool that incorporates internal (time tracking, project management, wikis, company news and insights, and information on internal processes) and external (Basecamp, Salesforce, social media insights and management,
and search engine optimization insights about the corporate website) into one dashboard. Treefrog aims to revolutionize business management with Mergini and the current project will be integral.

Designing Social Games to Maximize Engagement and Healthy

IgnitePlay is developing a social media package which will make healthier living more fun and easier. An

important component of this package is a social game and reward system that encourages users to make

changes in their lifestyle. This project will involve the development of a game design (in terms of a

prototype or series of prototypes) which will help:

1. attract and engage users,

2. promote virality (spread to other users),

3. promote stickiness (ability to sustain users),

4. provide incentives for people to engage in healthier behaviours, and

5. foster a sense of community

This design will be validated through user feedback. The outcome will be a design document for the final

production of the game that will be developed and published by IgnitePlay.