No manual template designing needed. Deep Learning methods detect the tabular areas and OCR them as tabular data. Sequential text analytics in NLP detect the entities (batch number, issue date etc.) across document irrespective of their position

Firms which have text data in the form of documents, reviews, articles, records of text description are good candidates for teX.ai ^TM. There are multiple modules which cater to different needs of different firms. Financial research firms with loads of documents wanting to extract tables; all B2C firms looking to sift through the reviews and grasp the key topics discussed; firms who want to classify their text description records which can be product description, calls, tickets, complaints, into categories – can all use teX.ai ^TM.