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Agentic AI Frameworks for Multi-Domain Intelligent Assistants
This project aims to help ALS improve how employees access and use information by creating an advanced AI assistant that can understand questions, search internal documents, and provide accurate answers across HR, training, and technical departments. ALS manages large amounts of complex material—such as lab procedures, policies, and technical reports—which can be difficult and time-consuming for staff to navigate. The proposed system will use modern AI and retrieval methods to unify these knowledge sources, reduce repetitive questions, and support faster decision-making. By developing this tool, ALS will benefit from improved efficiency, less reliance on subject-matter experts, and a more streamlined way for employees to find the information they need to work effectively.
Faculty Supervisor:
Jake Doliskani
Student:
Partner:
ALS Global
Discipline:
Computer science
Sector:
Mining
University:
McMaster University
Program:
Business Strategy Internship
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.