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November 14, 2019

DataRobot Partners with Kx to Deliver AI-Driven Solutions by Extending Time Series Capabilities

MILTON KEYNES, England, Nov. 14, 2019 — DataRobot, the leader in enterprise AI, has partnered with Kx to offer financial institutions and IoT-driven industries a comprehensive, scalable high-performance solution for applying AI to time series data. By integrating DataRobot’s Enterprise AI Platform with the Kx database platform kdb+—the world’s fastest in-memory time series database—the partnership, which was unveiled during the Kx Innovation Day at Aston Martin Red Bull Racing headquarters, allows consumers of market data to quickly generate actionable insights for agile, strategic business decisions.

“AI is rapidly reshaping all industries, but none more than financial institutions,” said Rob Hegarty, General Manager of Financial Markets and Fintech at DataRobot. “So much of the world’s market data is in kdb+ due to its powerful time series capabilities and performance. The integration with DataRobot—the world leaders in enterprise AI at scale—will accelerate ROI and separate financial markets institutions’ performance from their peers.”

In the AI-driven era, organizations everywhere need to develop strategies for implementing powerful machine learning models in order to stay competitive. This pressure is particularly acute in the securities industry, where financial institutions are constantly seeking ways to use cutting-edge technologies to accelerate research, find competitive advantage in trading, improve alpha generation, and manage risk. However, there are several hurdles when it comes to successfully deploying AI solutions. For instance:

  • The sheer volume of financial market data, which makes searching for signals and developing predictive models extremely challenging and time-consuming;
  • A reliance on manual, inefficient processes to build models for highly volatile and time-critical applications; and
  • Fragmented, distributed data sources across tools, teams, and platforms, making it difficult to source and combine data for use in the development and deployment of AI.

By integrating kdb+ with DataRobot’s Enterprise AI Platform—which features an Automated Time Series solution that automates every step of the time-aware machine learning process—market participants can solve these challenges much more effectively and quickly. The integration results in a single system to easily prepare, build, deploy, monitor, and manage sophisticated machine learning models and AI applications across asset classes and use cases.

“Financial services and IoT industries, with their ever-growing ubiquity of data, are primed for AI, and DataRobot and Kx are leading the way,” said Mark Sykes, Group CTO First Derivatives, COO Kx. “The combination of the two time series technologies creates a single solution that accelerates market players’ ability to draw inferences and build time-aware machine learning models that can make extremely fast and accurate predictions. Firms deploying the DataRobot and Kx time series solutions together stand to gain immediate and unprecedented scale and speed over rival firms.”

Financial institutions and IoT users can combine the flexibility and power of the kdb+ database to build sophisticated data acquisition and integration strategies that integrate with DataRobot’s vast array of powerful time-aware machine learning algorithms, eliminating the barriers to build, scale, and integrate AI-driven workflows. As a result, the speed of iteration increases greatly and time-to-value for AI applications is reduced dramatically, allowing firms to be much more effective, productive, and agile. Such solutions can be built, deployed, monitored, and maintained across a wide range of mission-critical applications, including trading, risk management, middle and back-office operations, compliance, and surveillance.

“The technology integration and partnership of DataRobot and Kx is lowering the barrier between market data and value generation by providing organizations with a single, cohesive solution that unleashes AI-driven forecasting with previously unheard-of efficiency and effectiveness,” said Jay Schuren, General Manager of Time Series at DataRobot.

“The kdb+ time-series database is the smallest and fastest in the world, known across the financial industry for its speed, scalability and performance, and we couldn’t imagine a better partner to integrate with than DataRobot,” said Kx’s Sykes. “With the combined power of our two platforms, financial institutions worldwide are able to maintain their competitive edge in the AI era and innovate much more rapidly.”

To learn more about the DataRobot and Kx partnership, visit: https://www.datarobot.com/partner/kx/

About DataRobot

DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises competing in today’s Intelligence Revolution. DataRobot’s Enterprise AI Platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models. This platform maximizes business value by delivering AI at scale and continuously optimizing performance over time. The company’s proven combination of cutting edge software and world-class AI implementation, training, and support services, empowers any organization – regardless of size, industry, or resources – to drive better business outcomes with AI.

About Kx

Kx is a division of FD, a global technology provider with over 20 years of experience working with some of the world’s largest finance, technology, retail, pharma, manufacturing and energy institutions. Kx technology, incorporating the kdb+ time-series database, is a leader in high-performance, in-memory computing, streaming analytics and operational intelligence. Kx delivers the best possible performance and flexibility for high-volume, data-intensive analytics and applications across multiple industries. The Group operates from 14 offices across Europe, North America and Asia Pacific, including its headquarters in Newry, and employs more than 2,400 people worldwide.


Source:  DataRobot 

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