Vyasa Analytics Highlights Big Wins in 2018; Looks Ahead to 2019
BOSTON, Feb. 7, 2019 /PRNewswire-PRWeb/ -- Vyasa Analytics, provider of the life sciences and healthcare specialized deep learning analytics platform Cortex, highlighted a successful 2018 driven by achievements such as new partnerships, customer wins and accolades. The company is looking forward to continued success in 2019 with new initiatives, event participation and continued enhancement of Vyasa's deep learning solutions.
"2018 was a great year for Vyasa and with this momentum, 2019 is shaping up to bring even greater innovation and success for our team and customers," said Dr. Christopher Bouton, CEO & Founder, Vyasa. "We're eager to continue to push the limits and provide novel analytical capabilities to our clients. Moving into 2019, our focus continues to be on providing best of breed, deep learning solutions for our clients and their most valuable use cases."
To kick off 2019, Dr. Bouton was named a "Top 100 AI Leader in Drug Discovery and Advance Healthcare" in a report by Deep Knowledge Analytics. Also, Vyasa was featured in Built in Boston's 50 Startups to Watch in 2019, a hand-curated report featuring 50 digital tech companies poised for greatness in 2019 and beyond. The companies on the list are building disruptive products and driving value within their industries, including e-commerce, software, IoT, web or mobile, digital agencies, and more. Companies eligible for this designation have been running for five years or less, and as a group represent a diverse range in terms of funding status, job creation and stage of growth.
Vyasa capped off 2018 by joining Accenture's innovative new partner ecosystem, designed to help independent software vendors (ISVs) and life sciences companies work more effectively together to accelerate drug discovery efforts and improve patient outcomes. Accenture worked with a select number of ISVs and organizations - including Vyasa - to integrate their technology and content into Accenture's research platform, allowing life sciences companies to give researchers access to innovative resources. As part of the partner ecosystem, Vyasa's software -Cortex - securely connects to client-specific data sources residing in the Accenture cloud-based research platform, enabling researchers to run a range of advanced deep learning, A.I. analytics on image, text and small compound content.
Also in 2018, Vyasa received a $1.8 million loan from MassDevelopment's Emerging Technology Fund to help its efforts to scale the company's compute infrastructure in Boston and hire more in-state talent. Since its creation in 2003, the fund has provided $73.1 million in loans and guarantees to help cutting-edge companies locate or expand in Massachusetts. The MassDevelopment funding led to Vyasa being named to BostInno's 50 on Fire list in 2018, as well as Vyasa's partnership with Markley Group, New England's largest, most comprehensive mission-critical data center and provider of networking and cloud computing services. Vyasa selected Markley to house its GPU-based compute infrastructure.
Vyasa's partnership with Markley also follows the company's acceptance into the NVIDIA Inception Program, a virtual accelerator program that helps startups focused on AI and data sciences during critical stages of product development, prototyping and deployment. Through these achievements and efforts, Vyasa will be able to continue to grow its specialization in deep learning while providing higher performance capabilities for its clients in Boston and beyond.
For more information on Vyasa and its deep learning capabilities for the life sciences and pharmaceutical industries, please visit http://www.vyasa.com.
About Vyasa Analytics
Vyasa Analytics provides deep learning software and analytics for life sciences and healthcare organizations. Cortex is Vyasa's secure, highly scalable software platform for collaborative knowledge discovery and data analytics. Learn more about Vyasa and watch the Cortex explainer video at http://www.vyasa.com.
SOURCE Vyasa Analytics
