Enate unveils Intelligent Document Processing release for service operations
In a new update, Enate has introduced Intelligent Document Processing (IDP) to its suite of AI features, changing the landscape of operations management.
This development comes as an expansion of EnateAI's initial offering, launched in July, which focused on helping businesses leverage AI in operations through ready-to-use features such as sentiment analysis, data extraction, query automation and categorisation. The addition of Intelligent Document Processing significantly enhances EnateAI's capabilities, enabling businesses to efficiently categorise and extract data from electronic or scanned documents such as PDFs, word docs, and drawings.
Time saving with IDP
Traditionally, manual invoice processing of such documents consumed considerable time, with employees spending 3 minutes per page. IDP reduces this time to a mere 30 seconds per page, making it a game-changer for businesses dealing with large volumes of data. The applications of Intelligent Document Processing are vast, ranging from invoice processing and customer onboarding to managing purchase order forms and contracts.
To illustrate the time-saving potential of IDP, consider a business processing 1,000 invoices monthly. Manual processing, taking 3 minutes per invoice, would require 50 hours of effort. With Intelligent Document Processing reducing the processing time to 30 seconds per invoice, the total time spent is reduced to 8 hours, resulting in a significant saving of 42 hours.
Advantages of IDP
One of the key advantages of IDP lies in its ability to eliminate the inefficiencies and errors associated with manual document handling. The cumbersome process of data entry for invoices, contracts, and forms is streamlined, saving valuable time and resources. By integrating IDP into the EnateAI platform, businesses can optimise their workflows, ensuring seamless and accurate document management.
Powered by Microsoft Azure, EnateAI's IDP feature simplifies the entire document processing cycle. The platform scans the document, extracts the required data, and assigns a confidence score based on the accuracy of the extracted information. If the confidence score falls below the threshold, the document is forwarded to a validation station, allowing human intervention to rectify any discrepancies.
What sets EnateAI apart is its seamless integration within the existing Enate platform. Unlike standalone providers, businesses leveraging EnateAI benefit from a unified workflow that eliminates the complexities associated with third-party vendors and machine learning model training. The platform offers a range of features, including email categorisation, data extraction, form auto-population, sentiment analysis, language translation, and automated query handling.
EnateAI's efficiency was exemplified in a case study involving a prominent bank. Faced with the challenge of integrating disparate systems for IDP, the bank turned to Enate's platform, orchestrating all processes seamlessly. The platform's orchestration capabilities streamlined the workflow, transforming disjointed systems into a unified, efficient process. This underscores the unparalleled efficiency and productivity achieved by using Enate and EnateAI to orchestrate processes.