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SORBA.ai and PAR Systems Partner to Bring AI-Driven Intelligence to Advanced Automation and Life Sciences Manufacturing
The partnership enables customers to move beyond precision automation into predictive, adaptive, and continuously improving operations.
Mar. 31, 2026 at 12:19pm
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Advanced automation systems are being infused with AI-driven intelligence to enable predictive, adaptive, and continuously improving manufacturing operations.Today in JacksonvilleSORBA.ai, a leader in no-code industrial AI, has announced a strategic channel partnership with PAR Systems, a global automation engineering firm recognized for delivering custom manufacturing systems across life sciences, aerospace, nuclear, and advanced industrial sectors. Through this partnership, PAR Systems will integrate SORBA.ai's industrial AI platform into its automation solutions, enabling customers to layer intelligence on top of these systems and transform high-performance equipment into self-optimizing operational assets.
Why it matters
This partnership is particularly impactful in the life sciences industry, where even minor process variation can impact product quality, regulatory compliance, and batch yield. By combining PAR Systems' engineering depth with SORBA.ai's no-code industrial AI, the companies are enabling a new class of intelligent manufacturing systems, where automation is not only precise but continuously learning and adapting.
The details
PAR Systems has developed highly differentiated capabilities in areas such as laser-based manufacturing systems, automated assembly systems, and lab automation platforms, addressing the extreme precision, traceability, and repeatability required in life sciences and medical device manufacturing. The addition of SORBA.ai's industrial AI platform will enable customers to detect early signs of process drift, predict failures in high-value manufacturing systems, optimize throughput and yield, and apply machine learning models without requiring internal data science teams.
- The partnership was announced on March 31, 2026.
The players
SORBA.ai
A leader in no-code industrial AI, enabling operators, engineers, and subject matter experts to easily build predictive models, detect anomalies, optimize production, and deploy autonomous control systems using their own plant data, without requiring data scientists or complex ML infrastructure.
PAR Systems
A global automation engineering firm recognized for delivering custom manufacturing systems across life sciences, aerospace, nuclear, and advanced industrial sectors, with a focus on solving complex engineering challenges through novel automation solutions.
What they’re saying
“PAR Systems is known for delivering automation solutions in some of the most complex and mission-critical environments in the world, particularly in life sciences. By combining their engineering depth with SORBA.ai's no-code industrial AI, we are enabling customers to move beyond automation into true operational intelligence, where systems can predict, optimize, and continuously improve.”
— Bryan Thyken, CRO of SORBA.ai
“Our customers depend on us to deliver highly precise, reliable automation systems. Partnering with SORBA.ai allows us to extend that value by embedding AI directly into these solutions, helping customers improve performance, increase yield, and make better decisions using their operational data.”
— David Bustamante, VP of Engineering, PAR Systems
What’s next
The partnership between SORBA.ai and PAR Systems will enable the companies to collaborate on delivering next-generation solutions across life sciences, advanced manufacturing, and other high-value industries.
The takeaway
This partnership represents a clear shift in the future of automation, where precision is combined with intelligence. By embedding SORBA.ai's no-code industrial AI platform into PAR Systems' advanced automation solutions, customers will be able to move beyond reactive operations and into a new era of predictive and prescriptive performance, particularly in the critical life sciences and medical device manufacturing sectors.





