Quadrant engages in collaborative efforts with clients to conceptualize, design, strategize, and execute AI solutions spanning a range of technologies. Quadrant OCR model, a managed service offering involves harnessing the capabilities of pre-trained models such as CNNs, RNNs, and Transformers, often integrating them with other Azure AI services. This methodology enables us to deliver high-impact solutions driven by business value, leading to the creation of new revenue streams or operational cost savings for our clients. Existing models in general have a 70 to 75% success rate in data extraction from images and scanned documents, especially with tables. We've addressed this challenge by integrating the Microsoft Table Transformer model. This strategic enhancement has significantly boosted our table extraction accuracy to 90 to 95%, ensuring more reliable and precise retrieval of structured information. Quadrant model serves professionals in data engineering, data analysis, data science, and generative AI engineering. Their capacity to revolutionize data storage lies in efficiently converting physical documents into digital formats for integration into databases. Our solutions utilize various services such as Microsoft Table Transformer (TATR), OCR, Azure Blob Storage, Azure Portal, Azure AI services, Azure Document Intelligence and pgSQL DB to create a robust and efficient Table extraction model.

  WHAT'S THE VALUE? 1. High Accuracy: Quadrant OCR model excels in extracting tabular data with precision, achieving accuracy levels of 90% or more in comparison with other OCR models. 2. Enhanced OCR: This model improves Optical Character Recognition (OCR) for complex layouts, images, PDFs, and scanned documents. 3. Efficiency through Automation: Automated tabular data extraction with table transformers boosts efficiency, minimizing manual intervention and resource allocation. 4. Versatility Across Industries: Applicable in finance, healthcare, education, and more, table transformers offer versatile solutions for diverse data extraction needs. 5. Cost Savings: Automation and efficiency contribute to reduced time and resources, resulting in cost savings, particularly beneficial for handling large volumes of data. 6. Flexible and customizable: Configure the model to extract specific data and integrate seamlessly with your existing systems.

USE CASES:

• Customized BOT Building: This process automates the extraction of details from legal documents using transformer tables, enhancing the understanding of complex legal language for more efficient legal analysis. • Financial Report Analysis: Leveraging transformer-based tables to parse financial reports allows for the extraction of crucial financial metrics, thus enabling a more structured and insightful financial analysis. • Medical Record Analysis: By applying transformer table extraction techniques to medical records, structured data is efficiently extracted, significantly improving the analysis and management of health information.

Unlock next-level data extraction with our advanced Table Extraction Model. Contact us to revolutionize your data processes and efficiency.