“Our Fall 2017 release further enables industrial customers in industries such as oil & gas, maritime and utilities to rapidly connect machine learning models, live data sources and business decision-makers through flexible, easy-to-use software,” said Tor Jakob Ramsøy, Founder, and CEO of Arundo Analytics.
The Fall 2017 release follows the successful introduction of the Arundo suite to heavy industrial users starting in 2016. Arundo’s customers and partners include Statoil, the Norwegian national oil company; Carnival Cruise Line, the world’s largest passenger shipping company; and SICPA, the leading provider of security and authentication services to national governments worldwide.
“Industrial customers operate capital-intensive legacy assets that are often decades-old,” said Jeff Jensen, Chief Technology Officer of Arundo Analytics. “Allowing our customers to connect to these assets through Edge Agent and inform better business decisions in remote or disconnected operating environments is core to Arundo's vision to transform heavy industry through data-driven insights.”
New Features in Fall 2017 Release
Arundo Edge Agent enables industrial analytics in rugged, remote or disconnected environments. New features and functionality in Arundo Edge allow users to:
- Quickly and easily install Edge Agent on Windows, Linux or Mac OS devices
- Support highly distributed architectures with offline buffering
- Use on-Edge compute chains for pre-stream processing of “virtual” or calculated sensors
- Directly access a local, web-based interface including streaming visualization
Arundo Composer allows companies to quickly and easily deploy desktop-based machine learning models into the Arundo Fabric cloud environment through a single command line. Composer also enables companies to create and manage live data pipelines and integrate such pipelines with deployed data models. New features and functionality in Arundo Composer allow users to:
- Scale deployed models and view logs
- Create and manage live data pipelines
- Rapidly prototype models locally before live deployment
- Auto-render data model user interface upon deployment
Arundo Fabric is the cloud-based hub for data models, enabling connections between data models published from Composer, streaming data from Edge Agent and static data ingested from other sources. New features and functionality in Arundo Fabric allow users to:
- View master lists of tags and sensors streaming data in real-time
- Access real-time status for deployed models
- Tie into existing interfaces and applications through APIs
- Use federated or out-of-the-box user authentication
Ellie Dobson, VP Data Science at Arundo Analytics, noted, “Arundo Composer, together with Arundo Fabric, automates the significant work and technical infrastructure required to turn desktop data science models into enterprise-scale machine learning applications. This software enables data scientists to focus on data science, rather than spending weeks on software engineering, model front-end development, or other issues, or coordinating with IT administrators, software developers, or DevOps/reliability engineers in order to publish machine learning models to the cloud.”
About Arundo Analytics
With offices in Oslo, Houston, and Silicon Valley, Arundo Analytics provides cloud-based and edge-enabled software for the deployment and management of enterprise-scale industrial data science solutions. Arundo's software allows industrial companies and other organizations to increase revenue, reduce costs and reduce risk through machine learning and other analytical solutions that connect industrial data to advanced models and connect model insights to business decisions. In 2016, Arundo graduated from Stanford University’s StartX accelerator program, and has subsequently received investment from the Stanford-StartX Fund. In 2017, Arundo was named to the MIT STEX25 by the Massachusetts Institute of Technology Startup Exchange (MIT STEX), which recognizes select companies from an elite pool of more than 1,000 MIT-connected startups, distinguished by early commercial success, as being particularly well-suited for industry collaboration. For more information, please visit www.arundo.com, or follow Arundo Analytics on Twitter @arundoanalytics.