Automatic Document Classification and Indexing requires the deployment of proprietary software packages that handle three critical tasks of the process which are, document scanning, the creation of a database and the criteria for documents classification. Each one of these tasks is achieved through the use of individual and unique approaches to software development.
We bank on open source platforms that are heavily optimized for enterprise use to integrate the following functionality into our software solution:
- Image and Text-based Scanning and data mining
- ‘Self-learning’ document indexing and classification algorithms using Machine Learning, Cognitive Computing and Deep Learning Modules
- Big Data and Predictive Analytics based database creation that forms the basic foundation for the document classification system
- Cloud computing capabilities
We use the diverse functionality of the Python programming language and the frameworks based on it, to deploy a highly scalable and lightweight solution for enterprises. We use the OpenCV library built essentially to achieve optical character recognition and Hadoop to compile, interpret and build the classification database for organizations. We also bank on MongoDB, Django and Luigi to develop the architecture of the database and to develop and customize the user interface for our solutions.