SYSTEMS AND METHODS FOR AUTOMATING GENERATION OF INFORMATION TECHNOLOGY PROJECT ESTIMATES USING ARTIFICIAL INTELLIGENCE/MACHINE LEARNING TECHNIQUES

Smart overview of the Invention

The disclosed system leverages artificial intelligence and machine learning (AI/ML) techniques to automate the generation of information technology (IT) project estimates. It addresses the inefficiencies and inaccuracies inherent in traditional estimation processes by utilizing large language models (LLMs) that interpret user queries in natural language. These models retrieve and analyze relevant data from a comprehensive knowledge repository to produce precise project estimates swiftly.

Background

Traditional IT project estimation is a time-consuming and often inaccurate process, heavily reliant on the expertise of key personnel. This process involves multiple stakeholders and can take weeks or months to complete, with estimates frequently needing revision. The manual nature of these estimations, combined with the potential for organizational knowledge loss, leads to unreliable forecasts and inefficient resource allocation.

System Functionality

The proposed system includes a processing unit with a processor and memory that executes specific operations. Key functions include receiving a user query that describes a new IT project and requests an estimate, maintaining a knowledge repository with relevant data, and training an AI/ML model using this data. The trained model then generates an accurate project estimate, which is provided as a response to the user query.

Technical Implementation

A non-transitory machine-readable medium is incorporated, containing executable instructions that facilitate the described operations. The system processes user queries, each containing multiple parameters, to generate project estimates using a large language model. This model accesses the knowledge repository, which includes system information, requirement documentation, financial data, and historical records, ensuring comprehensive and accurate estimations.

Methodology

The methodology involves a processing system that receives user queries, maintains a relevant data set, and uses an AI/ML model to generate project estimates. The system's ability to interpret and process complex queries allows for the automation of the estimation process, significantly reducing the time and resources required compared to traditional methods. This not only enhances accuracy but also streamlines project planning and funding decisions.