HOUSTON, TX & OSLO, Norway – Arundo Analytics, a software company enabling advanced analytics for industrial operations, today announced its expanded ability to bring data-driven insights to heavy industry. While companies in sectors such as consumer Internet deploy the latest machine learning techniques to improve business, many heavy industrial companies are unable to do so. This is due to a combination of legacy assets and challenging operating conditions. As a result, operational data often sits unused, or even lost. Arundo Analytics solves this challenge with cloud-based, edge-enabled software purpose-built for deep industrial data science and advanced analytics.
With offices in Palo Alto, CA; Oslo, Norway; and Houston, TX, Arundo combines high-technology expertise with deep industry knowledge. Arundo is a graduate of Stanford University’s StartX accelerator program, and a member of the Massachusetts Institute of Technology STEX25 group of MIT-connected startups. The Arundo team consists of 54 people, including 11 technical Ph.D.s, and boasts industry veterans from energy, maritime and other heavy industries, in addition to deep data science and software expertise.
“The benefits of machine learning, big data and the Internet of Things are no longer reserved for Silicon Valley,” said Tor Jakob Ramsøy, Founder and CEO of Arundo Analytics. “With Arundo, heavy industry can now benefit from advanced analytical insights, using industrial operating data to drive business decisions on an ongoing, repeatable basis in order to increase revenue, reduce costs and mitigate risks.”
Arundo Analytics Puts Data to Work
The problem of data going to waste is widespread. Forrester reports that 74 percent of companies want to be data-driven but only 29 percent are actually successful at connecting analytics to action. According to the Harvard Business Review, “cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions—and less than one percent of its unstructured data is analyzed or used at all.”
According to an internal study by Arundo Analytics, more than 95 percent of data generated from offshore rig sensors in the oil and gas industry may be lost or discarded rather than informing critical decisions. Arundo Analytics brings analytic insight to heavy industry by ingesting vast amounts of disparate industrial data (including from remote, rugged or intermittently connected “edge” locations such as ships or oil rigs) and connects this data to enterprise-scale machine learning models. Arundo’s software enables multiple new capabilities for industrial companies:
- Edge Data Ingest: Intelligently capture, stream and analyze data from remote industrial sites with simple, lightweight Arundo Edge Agent.
- Rapid Model Deployment: Publish machine learning models and connect to live data in minutes rather than weeks or months with fast, flexible Arundo Composer.
- Large-scale Models Management: Manage dozens or hundreds of published machine learning models (status, version, permissioning, output accuracy, performance, etc.) in Arundo Fabric.
- Push Machine Learning Applications at Scale: Deploy common industrial machine learning applications in areas such as asset utilization, equipment monitoring, logistics and scheduling, or safety in Arundo Fabric.