BANGALORE: MeshLabs is company driven by the challenge of finding solutions to unlock value hidden in text-based content for businesses across a variety of industries. MeshLabs’ content mining and analytics software is built for transforming any text-based content, regardless of its source, type, and channel of origin. Shantanu Gudihal, Co-founder, MeshLabs speaks to Vyas Sivanand about the company and its unique offering.
What is unique about the products and services offered by MeshLabs?
Companies have long been mining data to gain intelligence for constantly improving their businesses. But so far, the scope of it has been limited to structured data stored in traditional databases.
However, text-based and other forms of data such as audio and video, known as unstructured data, have been growing at a much higher rate than structured data. Leading data research firms such as IDC have estimated yearly growth of unstructured data within enterprises as high as 80 per cent compared to structured data growth at 20 per cent.
Processing text-based data in various natural languages requires sophisticated linguistic, statistic, and semantic computational approaches that are not available in standard business intelligence tool. The goal is to not only help businesses efficiently organise and better understand vast amounts of text data, in a manner not possible before, but most importantly discover meaningful, predictable, and actionable business insights.
Tell us about the technology used by MeshLabs?
At the heart of our offerings is the text analytics engine called eZiCORE. It is the primary engine of our solution stack.
It is a powerful semantic engine that automatically mines and analyses large volumes and varieties of content.
By applying a host of emerging technologies, including semantics and natural language processing, eZiCORE can transform your content into a
The index is an accurate categorisation of concepts, people, places, companies, products, and other specific entities with relationships.
How is the interest towards text analytics?
The company has seen steady increase in interest among companies to use text analytics technology to process vast amounts of textual data present in their support center notes, e-mails, surveys, financial reports, business documents in enterprise content management systems (ECM) among many other content sources and types.
Besides, tremendous attention to social media and other web based channels as indispensable sources for listening to voice of customer has helped turn the spotlight on text analytics as a viable technology for IT and business leaders.
Tell us about the products that you are planning to launch in the coming years?
We will continue to build on our text analytics focus. We are enabling What-if and dependence tree modules into our platform.
Machine learning systems with a strong focus on unsupervised learning is something we are building capabilities. Multiple language capability with transliteration tools keeping Sanskrit for byte-code processing.
We will very soon come up with a capability for the developers to access our platform with the API support. With this developers will have the power of text analytics delivered to their applications over cloud.