SymphonyAI has released a set of artificial intelligence (AI) “copilots” for frontline workers.
The new tools include three “role-based” copilots that offer “enhanced human-like interaction” beyond just standard data analytics and analysis “to understand what happened, why, and more importantly, anticipate future events,” the AI software-as-a-service (SaaS) firm said in a Tuesday (Nov. 14) news release.
Among the copilots is the “Plant Performance Copilot,” which uses natural language in a chat format and can recommend actions and forecast “plant performance through contextual, proactive insights and automated workflows.”
The “Digital Manufacturing Copilot,” meanwhile, combines workflow, production and asset data to reveal ways to optimize production and prevent bottlenecks. The tool’s generative AI also lets plants run “what-if scenarios for production scheduling, boost throughput, and improve overall equipment effectiveness metrics.”
The “Connected Worker Copilot” scans manuals, guides, knowledge bases and other data to provide problem-solving recommendations in natural language.
“SymphonyAI’s innovative industrial copilots move manufacturing beyond the limits of today’s analytics to a powerful factory of the future using predictive insights to anticipate and mitigate production risks and dramatically reduce maintenance costs,” said Prateek Kathpal, president and CEO of SymphonyAI Industrial.
“Our suite of industrial copilots turns the impossible into the possible with previously unimagined transformations in manufacturing efficiency, uptime, quality, and decision-making.”
The launch comes less than a week after the debut of SymphonyAI’s industrial large language model (LLM), designed to speed industrial transformation on a large scale.
As PYMNTS wrote last week, the SymphonyAI Industrial LLM was trained on an industrial dataset consisting of 3 trillion data points, more than 500,000 machine tests, 150,000 components and 80,000 different assets.
The Industrial LLM is hosted on Microsoft Azure and connects and contextualizes manufacturing operation information from everything from individual assets to global multi-plant operations, according to a company news release.
The company says this offering acts as a self-contained intelligence source to address asset performance and reliability queries. It provides operators and plant managers with context-aware data by gleaning insights from events, sensor data, asset details, work orders and other data sources.
This is happening at a time when — per PYMNTS Intelligence — 84% of companies think generative AI will positively impact the workforce. Elon Musk, meanwhile, has said that the technology will “render all jobs obsolete.”
“But for that future to come to fruition, organizations will need to overcome many obstacles to build out their own AI models,” PYMNTS wrote earlier this month.
“For one, with most companies still relying on technologically outdated legacy systems, establishing the infrastructure alone needed to accommodate AI systems can be a tall task for many businesses.”