Press Release (ePRNews.com) - SAN JOSE, Calif. - May 05, 2017 - OpsVeda, the leading provider of Operational Intelligence SaaS solutions, today announced that the United States Patent and Trademark Office has granted the company a patent, covering a machine self-learning method for deep assessment of the impact of events across the enterprise supply chain. The invention (US Patent No. 9,639,595) brings an automated method of self-learning to detect and report exceptions to a plurality of real-world processes, spanning a plurality of live transactions, activities, and things across an extended enterprise supply chain, in real-time.
OpsVeda continues an inspired journey, with a string of go-lives, customers expanding their footprint on the platform and now award of this patent. The momentum from 2016 continues to be strong. Detecting opportunity and risk situations in everyday business execution can be complicated – more so with the supply chains becoming deeper, and need for optimization becoming stronger. Intuition of team members alone, coupled with stale BI and departmental reports has never been enough to predict supply chain disruptions, or to respond to execution opportunities.
The OpsVeda system ingests current business process objects and activities into a process-agnostic data store (PADS), and analyzes the events as they occur. It allows for an automated mapping of extended operations processes and supply chain transactions. Associated exception scenarios are detected using machine learning techniques and/or user-defined rules. Thus, the system helps recognize anomalies and exceptions, and recognizes patterns in current and past process execution data, monitors Key Performance Indicators (KPIs) and trends thereof. The system can use these methods to learn and predict impending business issues on a continuous basis. Further, the system also provides operations teams with insights that can help them during engagements with customers, vendors and towards other tactical decisions.
“We all long for simplicity, and automation, and now the machine is here to help. Business processes come with unavoidable complexities, especially in the context of multi-tiered supply chains. It is vital that any data analysis factors in the nuances of the underlying processes,” said Sanjiv Gupta, CEO of OpsVeda and one of the inventors. He added, “With OpsVeda, we have simplified the underlying data structure without losing sight of the process details. This includes automated analysis of the data and early detection of exception scenarios. This facilitates proactive detection and optimization of business outcomes. Early adopters such as Western Digital and Global Brands Group recognized this innovation, and have enjoyed multiple years of successful execution, powered by OpsVeda. This patent award merely re-affirms this innovative thinking, and our untiring refinement of the platform over the past 5 years.”
“Whether one relies on heuristics-based configured rules or machine-learned patterns to predict disruptions, the first step is making sure that the complexities of the process is comprehensively reflected in the data model. Our PADS approach solves this problem in a unique way, and is a game changer,” said Dinesh Somani, VP of Cloud and Platform Architecture at OpsVeda and a co-inventor. “The architecture not only facilitates consistent ingestion of event streams from diverse processes, but it also enables establishing linkages between various data-points in an automated manner supported by machine learning techniques. This means users focus on business optimization, and not on data issues or myriad IT tools,” Dinesh explained.
OpsVeda is an enterprise software company providing a real-time operational intelligence platform with machine learning capabilities. Through its powerful insight-to-action solutions, it delivers predictive visibility into opportunities, risks, process exceptions and metrics, to business users across order fulfillment, supply management, manufacturing, logistics and retail operations. OpsVeda customers span the consumer packaged goods, food and beverage, fashion and retail, life science, manufacturing, and high-tech industries.