New integration empowers teams working with the fastest time series database to deliver time-aware AI and machine learning initiatives at scale and speed
DataRobot, the enterprise AI company, recently announced that it has partnered with Kx to advance financial institutions and IoT-driven industries with a comprehensive, scalable, high-performance solution for applying AI to time series data.
By combining DataRobot’s Enterprise AI Platform with the Kx database platform kdb+ the in-memory time-series database, the partnership, which was revealed during the Kx Innovation Day at Aston Martin Red Bull Racing headquarters, provides consumers of market data to produce actionable insights for agile, strategic business decisions quickly
“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.”
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In the AI-driven era, organizations everywhere require to develop strategies for implementing robust machine learning models to stay competitive. This requirement is especially acute in the securities industry, where financial institutions are continually 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 extraordinarily 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.
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“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 significantly, 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 are 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.
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