Artificial Intelligence & Machine Learning Application

Our company is a platform for creating data products enabled by AI, and we want to leverage the latest technology to gain market advantage. Applications of this technology to build data products include recommendation algorithms, predictive analytics like lifetime values, fraud detections, cyber security analytics and classifications. We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to our existing dataset. Students will develop an AI / ML model related to any of the aforementioned applications. This will involve several different steps for the students, including: Conducting background research for specific problem domains (Will provide at the beginning of project) Analyzing the dataset (identify data requirements) Researching the latest AI / ML techniques and how they could be applied to our data. Developing an AI / ML model that provides unique outcomes or insights into our data. Providing multiple solutions that can be applied to solve the same problem. (Key is to build a "deployable" solution

Permit Compliance Prototype Development

Overview Quotograph is seeking to develop a prototype for its new product, PermitX — a solution designed to automate the building permit review process by analyzing blueprints and identifying whether they meet local building codes. This project will focus on creating a working prototype that allows users to upload blueprints, which will then be analyzed against code requirements from a selected jurisdiction. Objective The primary goal of this project is to create an initial version of PermitX that demonstrates the feasibility of automated code compliance checks. The prototype will serve as a proof of concept, helping Quotograph validate the technology before expanding to multiple jurisdictions. Scope of Work Develop a user-friendly web-based interface where users can upload blueprint files (PDF, JPEG, or CAD formats). Implement basic blueprint parsing capabilities to extract relevant architectural elements (e.g., room dimensions, wall structures, electrical layouts). Create a rules engine that checks extracted elements against a set of predefined building codes from one jurisdiction (e.g., Ontario Building Code or a U.S. municipality). Generate a compliance report that highlights potential code violations and provides brief recommendations. Provide backend infrastructure that allows seamless data storage and retrieval of uploaded blueprints and compliance reports. Ensure the prototype works across desktop and mobile web browsers . Deliverables A fully functional prototype with the following features: File upload interface Automated code compliance analysis Downloadable compliance report Simple dashboard for users to track uploads and results Documentation on the system architecture, tools used, and any API integrations. Recommendations for future development and scaling PermitX to support additional jurisdictions and code types. Technology Stack Frontend: React or Wix Velo (depending on feasibility) Backend: Node.js + Express Database: MongoDB or Firebase Code Parsing: OpenCV or Tesseract for OCR Code Validation: Custom rules engine built in Python Outcomes By the end of this project, the PermitX prototype will demonstrate how Quotograph can automate blueprint reviews for code compliance, paving the way for a fully commercialized product that accelerates the permit approval process and reduces manual review times.