Dream Weaver ERP Auditor

Inspired by the intricate layers of dreams in 'Inception' and the experimental nature of assembling disparate elements like in 'Frankenstein', this project 'Dream Weaver ERP Auditor' aims to create an AI-powered auditing module for ERP systems. Unlike traditional rule-based audits, this tool will leverage machine learning to identify subtle, emergent anomalies that might be missed by standard checks. Think of it like a highly sophisticated 'map locations' scraper, but instead of physical locations, it's scraping for logical inconsistencies and improbable data sequences within an ERP. The 'dreaming' aspect comes from the AI's ability to generate probabilistic scenarios of how data -should- flow and then flagging deviations that are statistically unlikely, much like how the mind might construct surreal but internally consistent dreamscapes. Users would feed historical ERP data into the AI, which would then 'learn' the typical patterns of transactions, user behavior, and data integrity. The AI would then generate 'dream reports' highlighting unusual sequences or outlier transactions that, while not explicitly violating a rule, are statistically improbable and warrant deeper investigation. This is niche because it focuses on predictive, pattern-based auditing rather than reactive, rule-based checks. It's low-cost as it can be built using open-source ML libraries and a moderately powerful computer, and it has high earning potential by offering a novel and more effective solution for data integrity and fraud detection within ERP systems, a crucial concern for businesses.