Nvidia

WekaIO has built the world's fastest parallel file system, designed to solve the performance challenges in AI deep learning and technical computing. Matrix, WekaIO’s flagship product, leapfrogs legacy storage infrastructures by delivering the highest performance, lowest latency storage at a fraction of the cost or traditional NAS. WekaIO's software provides a seamless hybrid cloud solution between on-premises data centers and the public cloud. WekaIO has customers in several high performance markets including autonomous vehicle AI training, genomics, financial modeling, EDA, software development, satellite imaging and media and entertainment.

H2O.ai, Inc. develops an open source machine learning platform designed to facilitate predictive analytics and artificial intelligence applications. The company offers several key products, including H2O, which allows users to conduct in-memory machine learning, H2O Driverless AI for automated machine learning, and H2O Wave, a framework for real-time AI application development. H2O.ai's technology is utilized by over 5,000 organizations across various sectors, including insurance, healthcare, telecommunications, marketing, financial services, retail, and manufacturing, to address challenges such as fraud prediction and customer churn. Founded in 2011 and headquartered in Mountain View, California, H2O.ai aims to democratize AI by providing accessible tools for data scientists and developers to efficiently build and deploy machine learning models. The company maintains a strategic collaboration with Alteryx, enhancing its capabilities in predictive analytics.

Domino Data Lab, Inc. offers an enterprise data science platform that supports both on-premise and cloud-based solutions for data analysis applications. The company's flagship products include Domino Cloud, a managed cloud infrastructure for running and scaling data models, and Domino On-Premise, which facilitates tracking, sharing, and auditing of analyses. Domino Data Lab serves a diverse range of industries, including financial services, insurance, media and technology, health and life sciences, manufacturing, retail, ecommerce, and consumer products. The platform is designed to empower data science teams, allowing organizations to manage and scale their data science efforts effectively. Notable clients like Allstate, Dell Technologies, and Bayer utilize Domino to enhance collaboration, accelerate research, and deliver impactful models. Founded in 2012 and based in San Francisco, California, Domino Data Lab was formerly known as Cerebro, Inc. and adopted its current name in February 2015.

Saturn Cloud, Inc. is a New York-based company that develops a data science platform aimed at enhancing the efficiency of data science teams. Established in 2019, the platform features a parallel computing library called Dask, enabling users to perform data science and analytics tasks effectively. Saturn Cloud provides tools for seamless collaboration, scalable compute resources, and easy analytics, allowing data scientists to work independently without relying heavily on development operations or data engineering teams. The platform also includes automation tools, such as one-click publishing and sharing, which streamline processes and reduce the time spent on traditional manual tasks. This comprehensive approach equips businesses with the necessary resources to develop and deploy data science models in Python efficiently.

DeepMap, Inc. specializes in high-definition (HD) mapping and localization solutions tailored for autonomous vehicles. Founded in 2016 and located in Palo Alto, California, the company addresses the challenges of mapping and big data management for Level 4 and Level 5 autonomous driving. Its platform provides essential capabilities including HD maps, centimeter-level real-time localization for diverse road types and conditions, and simulation data, which are crucial for enabling self-driving cars to navigate complex environments safely and efficiently. DeepMap boasts a talented team with experience from leading companies such as Google and Apple, and collaborates with automotive industry partners to enhance the safety and reliability of autonomous mobility.

VAST Data, Inc. is a New York-based company specializing in data storage solutions designed to simplify and enhance data management for various demanding applications. Founded in 2016, VAST offers a universal storage platform that utilizes Intel's Optane SSDs as a cache for data stored on quad-level cell (QLC) SSDs, effectively eliminating the need for complex storage tiering and traditional hard disk drives. The company's all-flash storage system consolidates multiple applications, catering to sectors such as animation, deep learning, enterprise backup recovery, life sciences, and quantitative trading. By redefining the economics of flash infrastructure, VAST makes it feasible for organizations to store all their data on flash, thereby improving performance and operational efficiency. With an emphasis on scalability and productivity, VAST Data accelerates time-to-insight for workload-intensive applications, enabling businesses to leverage advanced analytics more effectively.

Obviously AI, Inc. is a company that specializes in cloud-based data science solutions, allowing users to perform complex predictions and analytics on their data by posing natural language questions without the need for coding. Founded in 2018 and located in Berkeley, California, the platform utilizes data science and machine learning to interpret user inquiries and identify relevant data for analysis. Once the data is gathered, it is processed through machine learning algorithms to generate predictions. This approach enables non-technical business analysts to quickly and effectively make informed decisions based on their historical data, facilitating better business strategies and customer targeting.

Parabricks provides high performance genomic analysis that can analyze whole human genome under an hour compared to days. Using state-of-the-art GPU acceleration and machine learning, users can significantly increase the throughput of their centers. By providing patient treatment based on their genomic variations, such personalized treatment will transform healthcare practices.

WekaIO has built the world's fastest parallel file system, designed to solve the performance challenges in AI deep learning and technical computing. Matrix, WekaIO’s flagship product, leapfrogs legacy storage infrastructures by delivering the highest performance, lowest latency storage at a fraction of the cost or traditional NAS. WekaIO's software provides a seamless hybrid cloud solution between on-premises data centers and the public cloud. WekaIO has customers in several high performance markets including autonomous vehicle AI training, genomics, financial modeling, EDA, software development, satellite imaging and media and entertainment.

Chosen AI aggregates HR data to generate skills and capability insights that allow businesses to be predictive in their workforce planning. Organisations are expected to make data-driven decisions on their people but are challenged with trying to draw relevant insights from messy, subjective and fragmented data. We have built a technology and data platform that uses Natural Language Processing and Deep Learning to identify proven skills and the context behind where and how they learnt them. The platform allows organizations to discover and understand their aggregated employee data to identify skill gaps, predict hiring needs and promote internal mobility. Founded in 2018, to solve the 'post and pray' reactive recruitment process most large organisations are subject to. It is now partnered with a range of blue-chip enterprises. Chosen AI has raised £650,000 Venture Capital Investment from Ascension Ventures, Half Court Ventures, the Founders Factory and leading UK Business Angels. Chosen AI joined the Founders Factory Accelerator programme in early 2018, is a member of the NVIDIA Deep Learning & AI start-up incubator and in 2019 was selected for the Tech Nation Applied AI growth programme. It was also identified by Forbes as one of the UK's most promising AI startups.

ABEJA, Inc. is a Japanese company founded in 2012, specializing in artificial intelligence software tailored for the retail and manufacturing sectors. Based in Minato-Ku, the company integrates advanced technologies such as IoT, big data, and deep learning to facilitate comprehensive data analysis. ABEJA offers a cloud-based platform that supports the entire machine learning and deep learning pipeline, encompassing development, deployment, and operation. Its services include data collection, analysis, automation, prediction, simulation, and visualization, all customized to meet the specific needs of various industries, particularly retail and manufacturing.

BlazingSQL, Inc. develops an open-source, GPU-accelerated SQL engine designed to improve database management and query execution. The company offers BlazingSQL Notebooks, a cloud-based platform that provides users with a managed Jupyter environment equipped with a CUDA GPU and pre-installed, GPU-accelerated Python packages. This platform enables efficient querying of various file formats, including CSV, JSON, Apache Parquet, and Apache ORC, by leveraging Apache Arrow to run queries directly in GPU memory. Established in 2015 and headquartered in San Francisco, California, with an additional office in Lima, Peru, BlazingSQL aims to deliver fast and user-friendly database solutions that enhance performance and simplify setup for users.

Leveraging general-purpose computing on GPUs, FASTDATA.io has developed its PlasmaENGINE®, a high-performance computing software engine, to exploit the massively parallel processing capability of NVIDIA’s GPU platform. The PlasmaENGINE® accelerates stream processing up to three orders of magnitude faster, while simultaneously cutting power and space requirements in the data center by more than 90%. The company was founded in 2016 by Alen Capalik. FASTDATA.io, Inc. is headquartered in Santa Monica, California.

The IFDAQ (International Fashion Digital Automated Quantification) is the most advanced and powerful AI system that provides quantitative market values for anyone and everything in the fashion and luxury industry. The IFDAQ values come from an intelligent ecosystem that creates a high-dimensional virtual image of the fashion industry and measures the effective market value based on the relative performance in the industry. Unprecedented scientific in-depth analytics and infinite insights tell you the real market and benchmark value, power, trend and influence of everything that counts in fashion: from the fashion group to their brands ad campaign, from the the fashion model to the fashion magazine – right down to the value of a single catwalk run or the fragment of an image. IFDAQ focuses on the development of artificial intelligence solutions to obtain analytics and research about the fashion industry. IFDAQ was a research project that started in 2008 and turned into a startup venture in 2016.

ABEJA, Inc. is a Japanese company founded in 2012, specializing in artificial intelligence software tailored for the retail and manufacturing sectors. Based in Minato-Ku, the company integrates advanced technologies such as IoT, big data, and deep learning to facilitate comprehensive data analysis. ABEJA offers a cloud-based platform that supports the entire machine learning and deep learning pipeline, encompassing development, deployment, and operation. Its services include data collection, analysis, automation, prediction, simulation, and visualization, all customized to meet the specific needs of various industries, particularly retail and manufacturing.

OmniSci, Inc. specializes in accelerated analytics solutions powered by graphics processing units (GPUs). Its analytics platform enables users to interactively query and visualize data, facilitating data science workflows across vast datasets. This technology is utilized by various sectors, including automotive, insurance, investment management, logistics, media, oil and gas, pharmaceuticals, telecommunications, utilities, and public services. The platform stands out by allowing organizations to derive insights from data far beyond the capabilities of conventional analytics tools. OmniSci's origins trace back to research at Harvard and the MIT Computer Science and Artificial Intelligence Laboratory. Established in 2013 and headquartered in San Francisco, the company has formed strategic partnerships with several prominent investors and firms, including Google Ventures, In-Q-Tel, and NVIDIA. OmniSci aims to support both business and government entities in leveraging data for informed decision-making.

OmniSci, Inc. specializes in accelerated analytics solutions powered by graphics processing units (GPUs). Its analytics platform enables users to interactively query and visualize data, facilitating data science workflows across vast datasets. This technology is utilized by various sectors, including automotive, insurance, investment management, logistics, media, oil and gas, pharmaceuticals, telecommunications, utilities, and public services. The platform stands out by allowing organizations to derive insights from data far beyond the capabilities of conventional analytics tools. OmniSci's origins trace back to research at Harvard and the MIT Computer Science and Artificial Intelligence Laboratory. Established in 2013 and headquartered in San Francisco, the company has formed strategic partnerships with several prominent investors and firms, including Google Ventures, In-Q-Tel, and NVIDIA. OmniSci aims to support both business and government entities in leveraging data for informed decision-making.

OmniSci, Inc. specializes in accelerated analytics solutions powered by graphics processing units (GPUs). Its analytics platform enables users to interactively query and visualize data, facilitating data science workflows across vast datasets. This technology is utilized by various sectors, including automotive, insurance, investment management, logistics, media, oil and gas, pharmaceuticals, telecommunications, utilities, and public services. The platform stands out by allowing organizations to derive insights from data far beyond the capabilities of conventional analytics tools. OmniSci's origins trace back to research at Harvard and the MIT Computer Science and Artificial Intelligence Laboratory. Established in 2013 and headquartered in San Francisco, the company has formed strategic partnerships with several prominent investors and firms, including Google Ventures, In-Q-Tel, and NVIDIA. OmniSci aims to support both business and government entities in leveraging data for informed decision-making.