Your browser is currently blocking notification.
Please follow this instruction to subscribe:
Notifications are already enabled.

AI And Deep Learning Firm ParallelDots Secures $1.4 Mn Funding From Multipoint Capital

AI And Deep Learning Firm ParallelDots Secures $1.4 Mn Funding From Multipoint Capital

This Brings The Total Funding From Multipoint Capital To $2 Mn In ParallelDots

Gurugram-based AI and deep learning solutions provider ParallelDots has raised $1.4 Mn in an additional funding round from Multipoint Capital, a U.S. based investment firm. This follows Multipoint’s earlier investment of $600K in early 2016 and brings the total funding from Multipoint Capital in ParallelDots to $2 Mn.

ParallelDots founders will use the funding to add to its technology team, support its expanding global footprint, and general operational expenses.

As stated by Gayatri Sondhi, Managing Director of Multipoint Capital, LLC. “The company fits our interest in making highly selective early-stage venture investments in emerging technologies. We have been impressed by ParallelDots technology, team, operational capability, and results orientation in the last eighteen months. We look forward to continuing to work with the Company.”

Ideated in 2014, ParallelDots is a venture led by Angam Parashar, Ankit Narayan Singh, and Muktabh Srivastava. The trio has developed novel algorithms and high impact products to solve real-world problems. The company licenses its proprietary AI technology to enterprises. ParallelDots solutions have already been deployed across various enterprises in different verticals like fintech, insurance, healthcare, and market research.

ParallelDots: The Journey From A Simple Tech Startup To A Deep Learning Platform

ParallelDots founders started their journey in January 2014 with incubation centre of TLabs. During the inception, they worked with online publishers to create timelines for any event using their archived content. For instance, if it were a news website that was covering the ‘US Elections 2016,’ they could quickly gather all important content from the past in a timeline to give a fully immersive, comprehensive backstory.

However, they soon realised that to create accurate timelines they would need a really powerful technology. That was the time they started working on deep learning and soon pivoted themselves from creating just timelines to offering a complete stack of intelligent text analytic APIs to enterprises. These APIs can now offer different use cases depending upon the need of the enterprise.

“We are excited about our strong suite of proprietary AI technologies, novel products, and growing revenues,” said Angam.. “We are serious about developing winning AI products. That is why we start with research and build our own algorithms and datasets. We are AI-first and vertical agnostic as AI is a universal expertise, and sooner or later it will impact everything. We drive a virtuous cycle of well- defined problems, well-selected algorithms, and well-developed solutions.”

ParallelDots: Road Ahead For The AI And Deep Learning Platform

ParallelDots is currently leveraging the need of enterprises to harness hidden insights in the heap of data they have, with its AI and deep learning algorithms. ParallelDot’s clientele is spread across geographies and belongs to different sectors – such as finance, news and social media, enterprise, etc. owing to diverse use-cases of their technology.

In the near future, they want to continue building world-class technology as they explore to go deeper into AI. “We will continue innovating the existing products and building new products,” said Angam.

While the AI and deep learning industry in India is still at the nascent stage, we cannot deny the available opportunities and the extent of its applications in multiple industries. According to a recent report by MarketsAndMarkets, globally the deep learning market is expected to be worth $1.72 Bn by 2022, growing at a CAGR of 65.3% between 2016 and 2022. The major factors driving the deep learning market globally are the robust R&D for the development of better processing hardware and increasing adoption of cloud-based technology for deep learning.

At present, the most common use cases of deep learning can be found in image, text and audio processing. For instance,  Baidu’s speech-to-text services, PayPal’s approach to blocking fraudulent payments and Amazon’s product recommendations are some examples that can be quoted here. But, as per research firm Gartner, 80% of data scientists will have deep learning in their toolkits by 2018.

With ever increasing data and alongside the need for AI driven deep learning platforms, startups like ParallelDots are the need of the hour. However, the only challenge will be to ensure timely flow of revenues and funding as well as good talent to fulfill client’s need at an affordable cost both ways.