TRLUP – Building an AI-Driven Compliance Intelligence Prototype: Clause Classification, Regulation Mapping, and Policy Impact Detection

This project will develop a working prototype of an intelligent compliance assistant that leverages machine learning to detect regulatory risks in business contracts, map clauses to frameworks such as GDPR and PIPEDA, and generate plain-language summaries. The system will also track evolving regulations and intelligently suggest policy updates. By simplifying legal review, it enables Canadian SMEs in highly regulated industries to avoid fines, reduce operational delays, and stay confidently aligned with changing laws. Ultimately, the solution empowers small businesses to treat compliance as a strategic growth enabler rather than a legal burden.

Faculty Supervisor:

Tyler Charlebois

Student:

Partner:

DMZ Ventures Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Humber Institute of Technology and Advanced Learning

Program: