What does teX.ai TM offer?

Businesses today face challenges deriving insights from vast amounts of text across various sources. teX.ai TM helps produce structured data, metadata & insights by extracting data from text, summarizing information and classifying content.



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.


teX.ai TM is a SaaS product solution from Indium Software.

Indium Software is a leading provider of Digital Engineering solutions with deep expertise in Application Engineering, Cloud Engineering, Data and Analytics, DevOps, Digital Assurance and Gaming. Over the past decade, Indium has built strong relationships with over 100 clients-spanning ISVs, Global 2000 as well as born-digital companies. With over 2000 associates, Indium makes technology work for clients, driving measurable business value.

For more information, visit www.indiumsoftware.com

Schedule a demowith our experts and unlock the potential of your text!



Prioritize and address the focus areas by finding answers to the following questions:

Which topics are being discussed in your reviews and complaints?
What key phrases form these topics? What are the weights of these words?


Reduce the time in extracting tables from the documents.

How to extract the unstructured tables, images of tables, PDF tables out of the text maze in a document?


Save time and effort by identifying the categories from large volumes of content.

Some examples – How to categorize millions of products?
What are the labels for the complaints? Which department should be allotted for each ticket?


Market Endorsement


teX.ai TM in the news!

Our CEO, Ram Sukumar discusses teX.ai TM and the path ahead for teX.ai TM in the ever changing text analytics landscape.