This one startup is transforming unstructured content such as those in PDF, Word, ASCII formats into a structured, searchable and indexable output. So why does Stelae Technologies make it to AIM’s startup of the week? Because it is using artificial intelligence in doing so. The output of the unstructured content as processed by the company’s AI software- Khemeia™, can then be injected into Content Management, Big Data & Analytics and Content Mining solutions.
The AI software and its use cases
Witnessing a successful journey since its inception, the AI software by Stelae Technologies is currently being implemented at major enterprises and public sector entities across many verticals such as laws and legislation, media/publishing, financial services, e-commerce, and since 2014, in the aerospace and defense sectors.
In the industrial sector Khemeia™ has been enabling the optimization of content by transforming legacy technical content into S1000d, DITA, financial, legal, regulatory and compliance content, into Excel, XML, HTML or any user-defined data structure.
It uses the 4 step transformation process to yield desired results. Beginning with Content Analysis and extraction where it detects the content element such as section titles, numbers, header, paragraphs, hyperlinks, tables, graphics etc., it then does the Semantic Tagging.
This is followed by Structuring the content by splitting the document into relevant modules, creating the hierarchy, formatting bullet lists etc. to finally converting it into Customer Specific outputs.
The perks of KhemeiaTM
“KhemeiaTM automates the entire transformation process. It uses AI techniques to extract and semantically tag meta-data, structuring and hierarchically organizing information, generating table of contents and converting them to XML-based outputs – all in real-time”, explained Aruna Schwarz, the CEO of Stelae Technology who leads the team at Stelae.
Having an experience of more than 20 years in Product Management, Business Development and Marketing with leading Telecos and Content Management solutions vendors, Aruna’s most recent experience was at Rosebud Technologies – a content management solutions vendor in Paris, France, where as Head of Marketing for Europe, she was responsible for developing and launching a suite of Content Management products.
“It provides many advantages such as enabling the deployment of effective search algorithms, reuse of content and ensuring interoperability of heterogeneous documents”, said Pierre Fraisse, CTO, Stelae Technologies, who has worked in the field of document management, search, semantic and XML related technologies for over 25 years.
Home » Startup of the week | Stelae Technologies- Transforming Unstructured Content using AI
“That’s not all, its biggest advantage lies in it being a time saving process, as it can process 20 pages of documents in 5 minutes, compared to long hours (close to 36 hours) if done manually”, he added.
The Team and Accolades
Posing a team with a perfect blend of enterprise software skills gained in large corporations combined with deep technology and innovation, this innovative software company has won multiple awards, thanks to its outstanding technology. Some of the accolades it flaunts are- IBM Global Entrepreneur winner for India & APAC, Nasscom’s Emerging 10 companies, UKTI’s Global Entrepreneur Program (2015) and London & Partner’s India Emerging 20 in 2016.
Other important members of the team are Maria Shaio who is the VP Business Development with more than 20 years of experience in IT & Telecoms Sales and Business Development (hardware, software and services) and Sandeep Raizada, VP Operations, who comes with an experience of 25 years in managing delivery centres and customer projects across multiple locations in the US, Europe & Asia.
Provide your comments below
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures. Contact: firstname.lastname@example.org.