Built for
Web
Technologies
Artificial Intelligence
Industry
Insurance
Country
India

Project Highlights

Project Highlights

  • One of the prestigious insurance company Landmark Insurance approached Rydot Infotech with a significant challenge. The company is doing a manual conversion process, with a large amount of data every day, and struggling to maintain their documents and analyze them.
  • As a result, the company was facing a huge loss in terms of time and resources.
  • The company recognized the need to streamline its data processing and analysis workflows, as they hold large data of various insurance stakeholders such as SBI, BAJAJ Allianz, Cholamandalam, Reliance, Kotak Mahindra, HDFC and much more insurance policy pdf format.
  • However, to convert their extensive collection of raw data, stored in PDF format, into Excel format, they need a data extraction system.
  • Our task was to develop an AI-based system that could automatically identify and extract text and formatting from PDF documents, subsequently converting the data into a structured Excel format.
  • The successful implementation of this project would significantly enhance the insurance company's ability to process and utilize its data effectively.

Project Highlights

Our Solution

  • To address the insurance company's data conversion needs, our IT experts analyze the business problem in detail and plan for the solutions to design and deploy an advanced AI-powered system.
  • This system leveraged cutting-edge machine learning and natural language processing techniques to accurately identify, extract, and convert data from PDF documents into Data formats such as Excel, JSON, and API.

Our Solution

Here we develop a solution to make hassle-free data conversion

  • 1. Select the policy company name
  • 2. Tick the format of the data.
  • 3. Upload the file which needs to be parsed.
  • 4. Click on Save button to Extract to get insightful data

The key components of our solution were as follows:

Analyzing raw data

Our system worked on analyzing the big data and based on needs the system will separate the documents.

Analyzing raw data

Document Analysis

Our system employed advanced optical character recognition (OCR) algorithms to analyze PDF documents and extract text from them. It effectively recognized and interpreted various fonts, layouts, and formatting styles, ensuring accurate data extraction.

Document Analysis

Data Extraction

Using sophisticated text mining techniques, the system identified and extracted relevant data points from the PDF documents. It intelligently recognized and categorized information such as policy numbers, customer details, claims data, and financial figures, among others.

Data Extraction

Formatting and Structuring

The extracted data was then organized into a structured format suitable for Excel spreadsheets. Our system employed intelligent algorithms to ensure consistency, accuracy, and appropriate data formatting in the converted Excel files.

Formatting and Structuring

Quality Assurance

To guarantee the accuracy and reliability of the converted data, our solution incorporated robust quality assurance mechanisms. It included data validation checks, error handling, and reconciliation processes to identify and rectify any discrepancies or anomalies during the conversion process.

Quality Assurance

Our features

Our AI-based data conversion solution offered several key features that set it apart from traditional manual conversion methods:

Cloud-based technology

Data extractions

Efficiency and time savings

Accuracy and precision

Scalability and flexibility

Integration capabilities

Cost-effectiveness

Data Visualization

Track extracted pdf file details through Interactive Dashboard from Admin Panel.