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A Full stack web application to help the people working in the Accounts Receivable departments in their day-to-day activities.

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AI-Enabled-Invoice-Management-Web-App.

A Full stack web application to help the people working in the Accounts Receivable departments in their day-to-day activities.

Introduction

The Web App project titled ‘AI Enabled Fin-tech B2B Cloud Application’ was the task assigned to the trainee of HighRadius. The Web App was constituted in alignment with the four modules explored in the course of the HighRadius program. The application asked for development was a full-stacked model of a B2B Fin-Tech Management Dashboard that fetches data from a server and displays it through the integration of a front-end UI web application.

Requirement Specification

For Machine Learning domain: ● View the invoice data from various buyers, ● See various fields/attributes of the invoice(s) from a particular buyer. ● Perform Data Pre-processing on the invoice data. ● Get account-level analytics to easily visualize and interpret data – EDA and Feature Engineering. ● Get a prediction of when the invoice is going to get-paid.

For Web Application Development: ● To build a Full-stack Invoice Management Application using ReactJS, JDBC, Java, Servlets. ● Build a responsive Receivables Dashboard. ● Visualize Data in the form of grids. ● Visualize Data in the form of graphs. ● Perform Searching operations on the invoices. ● Add & Edit data in the editable fields of the grid. ● Delete data of selected rows in the predefined templates.

Project Description

Below are the major aspects of the application that are developed.

  1. Data Loading in DB: • A dataset was parsed,processed, and loaded in the database schemas.
  2. UI Representation of the data: • A responsive Ul that displays the invoice data loaded from the database. • The UI supports searching and pagination • The UI supports editing of some editable fields, adding a new row to the grid, deleting rows from the grid and advance search.
  3. Al Support in the application: • Suports predicting the payment date for one or more invoice(s).

Technologies Used

• HTML/CSS • JavaScript • ReactJS • Java Servlets • MySQL • MaterialUI • Python • Machine Learning

Description Images of the Project

• Landing Page • It is how the Web UI looks when we first load our website.

Screenshot (194)

• Add Modal • It is how the Web UI looks when we click on Add button on landing page. We can add the details of the new invoices and add it to the database. • It is active when no records are selected,else is disabled.

Screenshot (195)

• Edit Modal • It is how the Web UI looks when we click on Edit button on landing page. • It is active only when single record is selected,else is disabled. • We can edit the editable fields of the selected invoice and save changes to the database.

Edit Modal

• Delete Page • It is how the Web UI looks when we click on Delete button on landing page. • It is active only when more than one record(s) is(are) selected for delete,else is disabled.

Delete Modal

• Search Field • It is used to perform dynamic search in customer Id field

• Advance Search • It is how the Web UI looks when we click on Advance Search button on landing page. • The user can perform advance search on the basis of following fields • Customer Id • Invoice Id • Document Id • Business year • User can perform the advance search operation using combination of any of the fields

Advance Search

• Analytics View • It is how the Web UI looks when we click on Analytics View button on landing page. • The user can provide constraints for the following fields • Clear date • Baseline Create date • Due date • Invoice currency
Analytics View

• The image provided in the charts.png is how the graphs looks by providing constraints in the advance field form. Screenshot (181)

• Predict Button • It is used to predict the expected payment date of the selected invoices. • It is active only when more than one record(s) is(are) selected ,else is disabled. • It makes use of the machine learning model trained for prediction ,then updates the value in the database.

Conclusion

Preparation of the project was challenging and also enjoyable. The challenges ahead encouraged me to devote my time learning about the skills and also implement them in order to achieve the desired demand of the UI Application. The application developed by me caters to all demands as stated in the problem statement of the Web Application.

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A Full stack web application to help the people working in the Accounts Receivable departments in their day-to-day activities.

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