Sep 22, 2023
No image
Completed
DX using Computer Vision and NLP technologies to recognize various types of documents and extract necessary information
$50,000+
4-6 months
Estonia
2-5
Service categories
Service Lines
Artificial Intelligence
Big Data
Software Development
Domain focus
Transportation & Logistics
Programming language
JavaScript
Python
Frameworks
TensorFlow
Torch/PyTorch
Vue.js
Challenge
The client faced the challenge of using multiple document types for various business scenarios, which led to the need to digitize all paper documents and organize them based on client details. This means that the client had a variety of document types at their disposal, such as contracts, invoices, letters, etc., and each of these documents was used for specific purposes in different business situations. However, this diversity of documents created difficulties in managing them, as it required searching and analyzing a large number of paper documents.
The client faced the challenge of using multiple document types for various business scenarios, which led to the need to digitize all paper documents and organize them based on client details. This means that the client had a variety of document types at their disposal, such as contracts, invoices, letters, etc., and each of these documents was used for specific purposes in different business situations. However, this diversity of documents created difficulties in managing them, as it required searching and analyzing a large number of paper documents.
Solution
The client partnered with Muteki Group to create an AI solution leveraging Computer Vision and Natural Language Processing (NLP) technologies. This solution was designed to recognize diverse document types and extract essential information from specific fields. Its primary objective was to transform paper documents into digital format and categorize them according to the client's requirements. The solution possessed the capability to identify various document types and extract pertinent data from designated fields. As a result, it substantially enhanced the accuracy and efficiency of the information extraction process.
The client partnered with Muteki Group to create an AI solution leveraging Computer Vision and Natural Language Processing (NLP) technologies. This solution was designed to recognize diverse document types and extract essential information from specific fields. Its primary objective was to transform paper documents into digital format and categorize them according to the client's requirements. The solution possessed the capability to identify various document types and extract pertinent data from designated fields. As a result, it substantially enhanced the accuracy and efficiency of the information extraction process.
Results
- The project was completed successfully within the planned timeline, demonstrating effective project management and execution.
- The AI solution achieved an impressive accuracy rate of 87% in the text extraction process. This accuracy rate indicates the effectiveness of the Computer Vision and NLP technologies used in recognizing and extracting information from various document types.
- The most significant impact was the high level of client satisfaction. The fact that the client was fully satisfied with the outcomes indicates that the project met or exceeded their expectations. This not only reflects the technical success but also underscores the project's ability to fulfill the client's specific needs and objectives.
- The project was completed successfully within the planned timeline, demonstrating effective project management and execution.
- The AI solution achieved an impressive accuracy rate of 87% in the text extraction process. This accuracy rate indicates the effectiveness of the Computer Vision and NLP technologies used in recognizing and extracting information from various document types.
- The most significant impact was the high level of client satisfaction. The fact that the client was fully satisfied with the outcomes indicates that the project met or exceeded their expectations. This not only reflects the technical success but also underscores the project's ability to fulfill the client's specific needs and objectives.