Document Processing Platform for a Large Freight Forwarding Company

Industry: Supply Chain
Location: APAC Region

Introduction

The client is a prominent player grappling with a formidable challenge. The manual handling, validation, and integration of an immense volume of freight documents into their ERP/Legacy systems proved time-consuming and error-prone. This inefficiency hindered productivity and left a void in an organized data management system for users and their critical documents. Furthermore, tracking file activities and user statuses presented a substantial challenge.

Amidst this logistical labyrinth, a beacon of hope emerged in the form of a comprehensive solution. Tntra harnessed cutting-edge technology to revolutionize our client's operations, paving the way for a seamless, automated, and highly efficient document processing system.

This case study unravels the intricate journey from challenge to triumph. Through innovative techniques and a meticulously crafted platform, we streamlined manual tasks and significantly enhanced accuracy and user experience. Read the case study to explore how this transformative solution catapulted our client's efficiency, productivity, and revenue to unprecedented heights.

Technologies Used

Python
FlaskAPI
Ruby on Rails
AWS services(Lambda, Sagemaker, S3)
Machine Learning
MongoDB

Services Provided

Web Development
Software Testing
Support & Maintenance

Business Problem

Manually checking, integrating, and processing freight documentation for integration into their ERP/Legacy system was challenging for the client. Handling a sizable volume of documents manually required much time and was less effective.

There was a lack of a centralized data storage system where the logistics company could manage the users and their document data.

It was difficult for the client to track users' file activities and status.

The team had raw data in files with multiple extensions. It was difficult to ascertain the number of file types and list the possible files to extract.

The current OCR system was not good enough to provide support in both Chinese and English language.

Project Goal

Building a strong platform for automating a large number of manual tasks.
Making a system that reduces time, errors, and effort.
Option for tracking the uploaded data daily.
Finding out the possible errors and activity of every document.
Provision for the users to send data on the ERP system.
Add the ability to export document listings in CSV format.

Solution

The team created a single platform on which all document-related tasks can be handled easily.
We have implemented a system where users just need to upload documents, and the system will automatically extract data and store it in the database.
We built the system using different languages and services. We used Python for Machine Learning and Ruby for UI and ERP, along with AWS services like S3, Lambda, and SageMaker were used for automation.
The platform was made so that verified data was sent to ERP & they could get real invoice data.
The team has achieved 95% accuracy while processing thousands of files.

Business Impact

Due to automated document processing, the client was able to save more time & get high accuracy, which resulted in fewer chances of error.
The manpower was able to utilize their time for more productive work, incrementing their revenue.
Support for multiple languages will help them expand their reach to broad business spectrums.

Features

Have a look at the top features that our developers incorporated into the solution.

Machine Learning

It detected entities like the Invoice number and extracted the data from the document.

User Experience

Users can manage their files and their status. They can refer to the document when needed.

Verify and Send Data

Any user can send data to their ERP point or database by verifying it.

Manage Activity

Any user can manage all activities performed on the file, i.e., file uploading, verification of data, etc.

Tntra Diamond

Tntra's Diamond is a comprehensive approach to helping enterprises manage the constant interplay between Business Process Reengineering and Digital Transformation. Tntra’s domain specific methodologies lead to software services for mature systems and software product engineering for new requirements, further transitioning to a managed service model to ensure stability and scale.

Tntra's Diamond enables the enterprise to stay ahead of the transformation curve, while at the same time ensuring optimal business processes to meet the needs of the new economy.

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