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SymphonyAI Launches Generative AI Copilots for Smarter Operations and Increased Uptime


Businesses often look for ways to speed up operations and boost efficiency for their frontline workers. (Not always, but often enough.) We’ve seen the likes of mobile solutions equipped with specialized applications that are empowering frontline workers with real-time information and enhancing overall task management as well as the incorporation of wearable technology, such as smart glasses and smartwatches.

Then, there’s ongoing training initiatives through digital platforms and immersive technologies like AR and VR. Real-time communication tools, advanced data analytics and a commitment to safety measures round out the strategies businesses often use to foster a workplace culture that prioritizes employee well-being and embraces adaptability.

SymphonyAI, a provider of predictive and generative enterprise AI SaaS, is taking a different approach, however, with its inaugural suite of generative AI industrial copilots to help frontline workers speed operations and improve efficiency.

The three role-based copilots are Plant Performance Copilot, Digital Manufacturing Copilot and the Connected Worker Copilot. They provide enhanced human-like interaction so workers can get beyond standard data analytics and analysis to understand what happened, why and anticipate future events.

Plant Performance Copilot enables users (including plant managers, maintenance and reliability engineers) to uncover and implement recommended actions to enhance plant performance by using natural language in a chat format. This is done in place of querying databases, interpreting dashboards, or accessing knowledge repositories. It interacts across all relevant data sources for critical asset processes, and delivers targeted user assistance, recommends actions and forecasts plant performance through contextual, proactive insights and automated workflows. It also accelerates root cause analysis from generated anomalies, including quantified KPI impact of underperforming assets and processes, along with recommended remediations.

Digital Manufacturing Copilot streamlines and strengthens manufacturing operations by tying workflow, production and asset data together to unveil invaluable production process optimization and bottleneck prevention insights. Generative AI adds a more intuitive ability to run what-if scenarios for production scheduling, boost throughput and improve overall equipment effectiveness metrics.

Connected Worker Copilot can comprehensively scan machine manuals, procedures, knowledge bases and other sources of data to provide instant, contextual recommendations and information to users in natural language. This enables users to instantly identify and resolve problems without having to conduct time-consuming research or consult more experienced colleagues. Integrated with SymphonyAI Connected Worker, this copilot streamlines inspections, reduces rework and minimizes resource waste for frontline workers. Natural language access to troubleshooting guides, maintenance manuals and procedure documentation fosters smooth operations with clear insights into workflow metrics and assists new employees with a screen tap.

“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 copilots, embedded within SymphonyAI's IRIS platform, utilize Microsoft Azure OpenAI and an industrial knowledge graph to analyze diverse manufacturing data sources. These copilots, designed for manufacturing personnel, offer personalized assistance to boost efficiency by presenting data in natural language. They are adept at contextualizing information from digitized knowledge bases, allowing users to explore “what-if” scenarios and uncover actionable opportunities for enhanced operations, reduced downtime and improved overall productivity.

Edited by Alex Passett
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