Title:
AI Assist - ARP (Qualification and Data hybrid)
Agreement Number:
1028591
Agreement Value:
$40,200.00
Agreement Date:
Feb 10, 2025 - Apr 28, 2025
Description:
The Project will support the assessment of data quality and data sources for AI project development. The project may also characterize and document aspects of data for AI, Data Governance and end user design and experience, with the goal to identify/prioritize potential AI Revenue generating projects.
Organization:
National Research Council Canada
Expected Results:
The NRC IRAP Artificial Intelligence (AI) Assist Program aims to equip and support SMEs to incorporate AI into their core products and services and/or undertake scientific research, product development, testing, and validation. AI Assist aims to increase the number, the quality, and the competitiveness of Generative AI (Gen AI), Deep Neural Nets (DNN), and Deep Learning (DL) products created and delivered by SMEs.
Location:
Toronto, Ontario, CA M4S 1Y5
Reference Number:
172-2024-2025-Q4-1028591
Agreement Type:
Contribution
Report Type:
Grants and Contributions
Recipient Business Number:
888045945
Recipient Type:
For-profit organization
Recipient's Operating Name:
Xello, Anaca Technologies, Career Cruising
Recipient's Legal Name:
Xello Inc.
Federal Riding Name:
Toronto--St. Paul's
Federal Riding Number:
35090
Program:
Industrial Research Assistance Program – AI Assist
Program Purpose:
The NRC IRAP Artificial Intelligence (AI) Assist Program aims to equip and support SMEs to incorporate AI into their core products and services and/or undertake scientific research, product development, testing, and validation. AI Assist aims to increase the number, the quality, and the competitiveness of Generative AI (Gen AI), Deep Neural Nets (DNN), and Deep Learning (DL) products created and delivered by SMEs.
Coverage:
The AI Assist program is designed to help innovative SMEs navigate the challenges of developing and adapting generative AI (GenAI) and deep learning (DL) solutions and to assist SMEs with awareness, planning and execution in order to develop these technologies safely and ethically.