Case Study: Upmonth
Upmonth is a cutting-edge autonomous system streamlining document organization for investors and investment companies. It centralizes documents, applies tags, and enables instant retrieval using machine learning.
Industry | Fintech
Project Overview
Statistics show that inefficient file organisation and retrieval processes lead to sub-optimal time management. Upmonth offers a tailored solution, it centralizes documents and emails, applying contextual tags for effortless organization and retrieval. Leveraging AI and machine learning, it instantly locates files, boosting productivity and performance.
Key Findings
The following were the key findings engineers at Xeltec identified:
Understanding Tickers' significance
The team gained a thorough understanding of Tickers’ functionality, establishing a solid base for future development and growth.
System mapping techniques
Event Storming, Example Mapping, and Persona Analysis were employed to develop a holistic understanding of the system’s requirements, revealing gaps in functional and technical aspects.
Leveraging NLP techniques
Advanced NLP techniques extracted meaningful information from hedge fund names by deconstructing them into keywords, acronyms, and abbreviations, enhancing clarity and understanding.
Problem Statement
The following are some of the problems we encountered:
01
Inconsistent Fund Naming Patterns:
Inconsistent fund name patterns can cause confusion, disrupt search and comparison functionality, and degrade the user experience for investors and investment companies.
02
Lengthy and non-descriptive Tickers:
Lengthy and unclear tickers increase data entry error risk and slow fund identification and analysis.
03
Uniqueness concerns of tickers:
Duplicate tickers cause conflicts, data inconsistencies, and inaccurate reporting within the automated document management system.
Implemented Solution
The following are the solutions implemented to resolve these issues:
Architecture revamp & Database construction
The backend was overhauled for better performance and scalability. A REST API enables seamless system communication, while a robust database efficiently stores and manages tickers and investment documents.
Test-driven development and automation
Test-driven development and automation techniques ensured system robustness. AWS SES deployment enabled reliable and scalable email communication for automated notifications and emails.
Standardized Fund Names & Tickers
Fund names were broken down into components, and a custom algorithm generated unique, descriptive Tickers. A Django app and Admin dashboard enabled efficient Ticker management.
Results
Upmonth revolutionizes document management, unlocking efficiency, savings, and compliance for businesses. Its robust features include:
- Automated version control and access permissions
- Rapid information retrieval for accelerated decision-making
- Cost-effective solutions to minimize overheads and optimize resources
- Seamless collaboration and anytime, anywhere document access
