Developing A Retrieval-Augmented Generation (RAG) Framework for Enhanced Data Analysis and Insight Generation for Capital Allocation Decision-Making

The proposed project aims to enhance decision-making in capital allocation by integrating different AI techniques into a data processing system. The goal is to develop an intelligence platform that efficiently processes large amounts of financial data, using AI to uncover valuable insights. The program will have different parts that each works on specific tasks, including collecting data, retrieving data, ranking documents, and producing predictions. This approach will enable the customers to make data-driven and informed decisions of capital fund allocation. The expected benefit is an improvement in the organization’s ability to analyze market trends and allocate resources effectively, leading to better financial outcomes and a competitive advantage in the market.

Faculty Supervisor:

Yan Liu

Student:

Partner:

AltQ.ai

Discipline:

Computer science

Sector:

Finance and Insurance

University:

Concordia University

Program: