By Benoit Gourdon on Nov. 8, 2017
With latest version of Artificial Intelligence platform, Tellmeplus packages intelligence with every asset
Predictive Objects' minimal footprint runtime enables predictive models to run inside or close to the asset it supports while preserving consistency with global deployments.
Web Summit, Lisbon, 8 November 2017 - Tellmeplus, the specialist in Artificial Intelligence (AI) applied to Big Data, released today the latest version of Predictive Objects, the first AI platform for asset efficiency that packages intelligence with every asset.
In version 1.4, Predictive Objects leverages a new deployment capability for predictive models, that features a nano-footprint option capable of running on memory- and CPU- constrained connected objects and devices. Using the same technology stack as the one deployed on edge computing gateways and cloud servers, Predictive Objects run seamlessly and consistently on all types of assets, regardless of their level of computing power or their state of connectivity.
"Thanks to the use of innovative scalable time series oriented data storage, we were able to reduce the footprint required by Predictive Objects to a few hundred kilobytes only," explained Jean-Michel Cambot, founder and chief strategist at Tellmeplus. "With its transparent scalability from very large and dense time series to smaller ones, the same technology stack is also deployed on much more powerful systems, while guaranteeing complete consistency across platforms."
Packaging intelligence with every asset
Thanks to their ability to get deployed and embedded on any platform or runtime, Predictive Objects 1.4 packages intelligence with every asset, providing a combined view of the asset, its performance and evolution over time.
"Asset intelligence drives the strategy of any organization, regardless of industry or focus," indicated Benoit Gourdon, chief executive officer of Tellmeplus. "Being able to closely package predictions with the asset itself requires the ability to run predictive models in any type of technical environment, but also to gain a deep understanding of the characteristics of the asset and to associate these particular attributes to the produced predictions."
True multi-cloud deployment
In this new release, Predictive Objects also added the capability to provision and deploy predictive models concomitantly on several cloud platforms, but also to manage and monitor these deployments from a centralized, single front application. Models can run inside Amazon Web Services, Google Cloud Platform, Microsoft Azure, as well as a number of private cloud deployment platforms.
Founded by Jean-Michel Cambot, the original inventor of Business Objects, Tellmeplus leverages 5 years of research in the field of artificial intelligence applied to predictive analytics. Predictive Objects leverages Big Data & Meta Active Machine Learning to provide Automated Embedded Artificial Intelligence. Tellmeplus’ technology enables to put the intelligence where decisions need to be made: in the objects and at the edge of the network.