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AquaMesh Builds Physical AI to Help Industrial Facilities Catch Costly Problems Early

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The San Diego industrial AI company combines proprietary sensing with existing plant data to reduce production loss, downtime and operating costs as it expands commercial deployments and raises a $3 million seed round.

SAN DIEGO - TelAve -- AquaMesh, a San Diego-based industrial AI company, is building physical AI designed to help industrial facilities produce more, waste less and prevent expensive problems before they happen. The company combines existing plant data with real-time sensing to detect process problems early, identify their likely causes and tell operators what to change.

The global water and wastewater treatment market is worth roughly $400 billion annually. In the U.S. alone, there are more than 55,000 food and beverage manufacturing establishments, just one of the industrial sectors AquaMesh is targeting.

Factories lose money when product escapes the process, equipment degrades, energy and water are wasted or changing conditions are caught too late. Unplanned industrial downtime costs an estimated $260,000 per hour on average. A single process problem can mean lost production, downtime, damaged equipment, excess energy use or thousands of gallons of wasted product. Yet many facilities still discover critical conditions through delayed lab tests, manual checks, indirect measurements or alarms that trigger only after a problem has developed.

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"Most facilities have a blind spot around what is physically happening inside their processes, and that blind spot is expensive," said Alex Towfigh, founder and CEO of AquaMesh. "We turn it into an economic advantage. At target facilities, these inefficiencies can represent $1 million or more in annual costs. The immediate value is straightforward: more production, less downtime, lower operating costs and fewer expensive surprises."

AquaMesh connects to the data a facility already collects, identifies where money is being lost and adds proprietary sensing when a critical physical or chemical condition is not currently measurable. From there, the platform works continuously to detect a problem, find its likely cause, predict the cost or operational consequence, recommend a response and verify the result.

The company is targeting 10 to 25% lower operating costs across water, chemicals, energy, labor and discharge.

The company participated in UC San Diego's Horizon Accelerator and is currently expanding its commercial industrial deployments. AquaMesh has conducted more than 200 customer interviews.

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"Once AI can reliably see what is physically happening inside a facility, it can move from recommending actions to optimizing operations automatically," Towfigh said. "That is the long-term opportunity. Autonomous facilities start with giving operators information they can trust and act on today."

AquaMesh is now raising a $3 million seed round and is seeking investors, industrial partners and strategic partners in automation, sensing and engineering.

Connect is sharing this announcement as part of its ongoing work to amplify the founders, companies and technologies advancing San Diego's innovation economy.

Learn more about AquaMesh: https://aquamesh.ai/

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