BOXX Deep Learning Workstation Demos Datalogue Software at GTC

Deskside System Equipped with Four NVIDIA Quadro GPUs Accelerates High Performance Computing Application

AUSTIN, TEXAS and SAN JOSE, CA, March 19, 2018—BOXX Technologies, the leading innovator of high-performance computer workstations, rendering systems, and servers, today announced that the APEXX W3 data science workstation will demonstrate Datalogue’s proprietary software designed to reconcile disparate data sets at BOXX booth #520 at NVIDIA’s GPU Technology Conference (GTC). Held through March 21 in San Jose, GTC is the premier AI and deep learning event, providing attendees with training, insights, and direct access to experts from NVIDIA and other leading organizations.  

“Datalogue delivers ROI for organizations by empowering them to make the right decisions faster,” Bill Leasure, BOXX VP of Marketing. “At BOXX, we also understand that time is critical. That’s why our NVIDIA-powered APEXX W3, purpose-built to accelerate software applications, and maximize productivity, is the ideal ROI solution for Datalogue and other industry leaders.”

A highly versatile platform ideal for deskside deep learning development, rendering, and other GPU-centric workflows, APEXX W3 features up to four NVIDIA® Quadro® GPUs, along with a single, 18-core Intel® Xeon® W processor. At GTC, The compact workstation will provide optimal support for Datalogue software demonstrations.

Using abstraction and machine learning technology, Datalogue provides telecommunications, finance, and pharmaceutical organizations with the tools necessary to reduce their time to data, resulting in better, faster decisions. Inside the BOXX booth, Datalogue is partnering with OmniSci a software company that uses GPUs to query and visualize big data. Datalogue will highlight their recent solution for Charter Communications, a leader in the telecommunications industry. In this case, the number and type of network machines involved, the required adjustments against billing/inventory datasets, and changing demands by management, required eight days to visualize the network. However, it was infeasible to improve the network since they were unable to see how it was performing. With their proprietary software solution, Datalogue was able to achieve less network overlap, a reduction of analysis time and higher visibility, a reduction of operator downtime, and higher customer satisfaction for a predicted ROI of $50 million.

 “In today’s enterprises, data scientists spend roughly 80% of their time preparing data,” said Datalogue CEO & Co-Founder Tim Delisle. “At Datalogue, we’re tackling data preparation by combining computer vision and natural language processing techniques. This allows our customers to quickly and accurately identify, classify, join, and transform relevant data to become truly data driven.”

“Data science, like so many other industries, requires state-of-the-art GPU performance that only NVIDIA can deliver,” said Bob Pette, Vice President, Professional Visualization, NVIDIA. “By integrating the latest NVIDIA Quadro RTX GPUs, BOXX provides optimal hardware support to companies like Datalogue which, in turn, better serves its customers with fast, accurate data essential to sound decision making.”       

For further information and pricing on the APEXX W3, contact a BOXX sales consultant in the US at 1-877-877-2699. Learn more about BOXX systems, finance options, and how to contact worldwide resellers, by visiting For dedicated, multi-GPU, cloud-based deep learning solutions, contact the BOXX-owned Cirrascale Cloud Services at (888) 942-3800 or visit .




About BOXX Technologies

BOXX is the leading innovator of high-performance computer workstations, rendering systems, and servers for engineering, product design, architecture, visual effects, animation, deep learning, and more. For 23 years, BOXX has combined record-setting performance, speed, and reliability with unparalleled industry knowledge to become the trusted choice of creative professionals worldwide. For more information, visit .