Case Study: Streamlined Supply Chain Financing Process
Project Overview
The project aimed to implement automation in key supply-chain financing processes for a leading debt financing firm specializing in funding promising startups and businesses. The objective was to streamline the manual human effort involved in these processes and transform them into an overnight automated process. The solution involved the development of a Machine-Vision/AI model to read invoices in image/PDF form and extract relevant fields such as Invoice Number, GST Number, Seller/Buyer Details, and Total Amount. This automation enabled our client to gather data in real-time, saving significant time and effort.
Project Duration
The estimated project duration for completion was six months.
The Problem
Prior to the implementation of the automation solution, our client faced challenges in their supply-chain financing processes. These processes required a significant amount of manual effort to read and extract information from invoices. This manual approach was time-consuming, prone to errors, and hindered real-time data availability.
The Goal
The goal of this project was to automate the key supply-chain financing processes and enable real-time data gathering for the client. The objectives included:
- Develop a Machine-Vision/AI model to read invoices in image/PDF format.
- Automatically extract relevant fields from the invoices, such as Invoice Number, GST Number, Seller/Buyer Details, and Total Amount.
- Streamline the process and eliminate manual effort, saving time and reducing errors.
- Enable real-time data availability for efficient supply-chain financing decisions.
User Research
- Conducted user interviews with client company's team to understand their pain points and requirements in the supply-chain financing process.
- Analyzed the existing manual process to identify inefficiencies and areas for improvement.
- Collected user feedback and conducted usability testing of the developed Machine-Vision/AI model.
Summary: Through user research, it was found that the manual effort involved in the supply-chain financing process was time-consuming and prone to errors. Real-time data availability was crucial for efficient decision-making. The implementation of an automated solution would save significant time, eliminate errors, and enable real-time data gathering.
Pain Point
The main pain point experienced by our client was the time-consuming manual effort required in the supply-chain financing process. Extracting information from invoices, such as Invoice Number, GST Number, Seller/Buyer Details, and Total Amount, was a tedious and error-prone task. Additionally, the lack of real-time data availability hindered efficient decision-making.
Solution Brief
Our solution involved developing a Machine-Vision/AI model that could read invoices in image/PDF format and automatically extract relevant fields. The key features of the solution included:
- Machine-Vision/AI Model: We developed a sophisticated Machine-Vision/AI model that utilized advanced techniques to read invoices accurately.
- Field Extraction: The model automatically extracted crucial fields from the invoices, such as Invoice Number, GST Number, Seller/Buyer Details, and Total Amount.
- Real-time Data Gathering: The automated process enabled real-time data availability, allowing client to make efficient supply-chain financing decisions.
Impact and Lessons Learned
The implementation of the automation solution enabled a significant impact on the client's supply-chain financing processes. The key outcomes of the project were:
- Time Savings: The manual effort of months' worth of work could now be transformed into an overnight automated process, saving significant time and resources.
- Error Reduction: The automated solution enabled elimination of errors caused by manual data extraction, ensuring accuracy and reliability in the supply-chain financing process.
- Real-time Data Availability: Solution enabled access to real-time data, enabling faster and more informed decision-making.
- Increased Efficiency: The streamlined process enabled improvement in overall efficiency, allowing the client to focus on strategic initiatives.
Through this project, we learned the importance of leveraging Machine Vision and AI technologies to automate manual processes and enable real-time data gathering. The successful implementation of the solution showcased the significant impact it had on streamlining supply-chain financing processes, leading to increased efficiency and improved decision-making capabilities.