A company under Convergence Partners, inq, has unveiled its Doc AI platform, which utilizes specialized deep learning optical character recognition- OCR technology to upload scanned documents or images of any type. The solution is capable of extracting essential fields and integrating them into an Excel file or database, aiding organizations in digitizing processes that were previously manual.
Doc AI features a built-in machine learning engine that continually learns and conducts predictive analysis of information. This ongoing learning and improvement process significantly enhance the accuracy of extracted data over time. Designed to accommodate various document types and use cases, the service empowers organizations to make sense of, process, and efficiently manage large volumes of unstructured data. With Doc AI, businesses can unlock new levels of efficiency and data-driven decision-making while simplifying previously manual and time-consuming processes.
Powerful and Comprehensive
Sales and Marketing Director at inq SA, Ralph Berndt says “Doc AI is a comprehensive system that goes beyond simply performing OCR or pulling relevant information. It is a powerful tool to help companies automate document processes and find insights throughout their large volumes of documents.”
By utilizing Doc AI, businesses obtain a document visibility score, enhancing their confidence in the extracted OCR. This extracted information can be effortlessly exported through an API or integrated into existing ERP solutions. The platform’s scalability enables companies to surpass OCR-based template methods and RPA-based memorization efforts, which prove less effective in handling changes across large document volumes.
Additionally, the Doc AI platform can be seamlessly expanded with customized add-ons to facilitate integration with existing organizational systems.
“Our flexible payment options also mean companies can choose between a flat fee or per-document rate depending on their specific requirements. Organisations can focus on quicker time to value for primary users and secondary consumers by focusing on developing applications and faster integrations. This is done using highly accurate extracted information and knowledge as opposed to the time-intensive process of updating rules, re-automating template management, and moving documents,” added Berndt