Grants and Contributions

This project will develop a self-onboarding system for the Firm's AI-enabled document intelligence platform that lays the foundation for scaleable purchase order processing and broader market adoption.

The purpose of this CanExport Innovation agreement is to support Canadian organizations to carry out activities related to pursuing opportunities that would lead to establishing new collaborative Research and Development (R&D) partnerships between the Recipient and foreign organizations in order to support R&D on the Recipient’s technology and advance its commercialization.

The primary goal of this initiative is to minimize risks associated with individual chip chemistries, ensuring their accuracy and reliability in measuring urine albumin and creatinine and serum cystatin-c and creatinine. By validating the performance of each biomarker against a well-established predicate device, we aim to confirm their suitability for clinical use.

Building upon Atmose’s significant development of its patented sensor (current at TRL 6), the proposed project will further advance the manufacturing process, optimize the design for scalability, increase Atmose’s production capacity and evaluate the sensor in increasingly challenging environments (TRL 7 to 9) to prepare for certifications and customer trials/sales.

As Armilla scales to a larger number of platform users, a productivity-enhancing feature is to use LLMs as risk copilots to assist in AI risk reporting, recommending testing controls, and keeping abreast with AI regulatory changes.

This project aims to create an AI-assisted trigger reporting for dairy farmers, comprehensive app AI integration, machine learning-driven outcome predictions (e.g. breeding outcomes), low code data access, and multi-site advisor dashboard.

Insight Medbotics is developing a robotic system that can significantly improve the efficiencies, reduce the produce time, and improve the accessibility of MR-guided prostate biopsies.

The company is planning to grow through developing digital monitoring of EPCM automated machines in order to improve predictive maintenance , and improving the durability and useful life of the electroplating electrode design.

Development of an autonomous acoustic data acquisition, detection and tracking suite for passive acoustic listening from uncrewed maritime systems to commercial product readiness. The developped suite will become an integral value addition to STL's thin-line towed array (TLTA) line COMPASS, and can also be combined with other systems.

Predict calibration parameters using AI for a semiconductor equipment with the goal of increasing yield, throughput and uptime