Grants and Contributions

Make the ORG networks and expertise available to assess, connect and validate mining companies’ interest in the technological innovation projects of Canadian SMEs to partner on a technology demonstration project that would be funded under the IRAP ecosystem initiative: Enabling the transition to Mining 4.0.

The project will test AI strategies applicable to automatic anomaly detection for turbomachinery, establish the ideal architecture and achieve quantitative technical objectives in preparation for the implementation of an AI solution.

This project will ensure that soluble microbicidal diperiodatoargentates developed at ILC can be made consistently with a scalable manufacturing method. The compounds will be characterized for antimicrobial activity, stability, and compatibility. The most promising compounds will be further developed towards commercialization, including formulation work, finalizing/scaling up the manufacturing process, and performing proof-of-concept/pilot testing of the materials for specific applications, such as sprays, flushes, dips or wipes in medical, industrial, and agricultural settings. The results of the work will be used to promote collaborations with other companies and support registration of final products with appropriate regulatory agencies.

The project aims to help small and medium-sized businesses in the beverage industry become more innovative and competitive. It does this by offering "pre-copacker" services to determine if their product ideas can be produced on a large scale. These services include refining product ideas and creating formulas that can be manufactured for test markets and sales. Additionally, the project provides business advice on market research, competitive analysis, and branding support.

The project will deliver a new integrated LED micro-array driver and control network, which represents a key building block in the firm's optical switch technology, for future applications (antenna structures).

Our AI-powered Quality Control for Production & Structuring Frontier Data Project focuses on developing and testing AI-powered Quality Assurance (QA) algorithms that can be customized to various data types and annotation tasks, enabling more flexible and targeted quality assessment. These algorithms will leverage existing machine learning models and novel QA techniques to automatically evaluate and enhance the quality of data annotations produced by our Human AI Trainers, resulting in an increase in data annotation accuracy and decreased data processing time.

The aim is to develop an adhesive tape application machine for automotive seals.

This project focuses on brokerages' FINTRAC compliance reporting obligations and tools for perational efficiencies.

The project consists of researching, selecting and integrating an innovation into the neurostimulation device developed by the firm. The innovation will thus lead to a better understanding of the effect of neurostimulation on the device user.

Seneca’s Centre for Innovation in Life Sciences (SCILS) will foster innovation in the biotechnology, personal care and cosmetics, and chemical industries across Canada with a comprehensive suite of concept-to-commercialization services.