Applying AI agents to industrial operations with UptimeAI (Ep. 242)
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The guest, Jag Yatu, founder and CEO of Uptime AI, reveals how AI agents are transforming industrial operations by cutting months-long troubleshooting processes down to hours. In one case, a petrochemical plant’s compressor failure—caused by unexpected crude composition changes—was diagnosed in just one hour using Uptime AI’s root cause agent, saving $10–15 million. The company’s suite of specialized agents tackles maintenance optimization, safety (HAZOP), and process yield improvements across oil and gas, chemicals, cement, and power sectors. Unlike generic AI, Uptime AI’s agents embed domain-specific expertise—like understanding PNIDs and equipment failure modes—enabling them to act as virtual experts. Yatu emphasizes that success comes not from chasing flashy AI trends, but from selecting high-impact problems, choosing the right partners, and empowering 'citizen champions' to drive adoption. With backing from major VCs and industrial giants like Yokogawa and ABB, Uptime AI is positioning itself at the forefront of agentic operations, aiming for an IPO as vertical AI agents explode across industries.
AI agents can diagnose complex industrial failures in hours instead of months, saving $10–15 million per incident.
Uptime AI’s agents embed domain expertise (e.g., PNIDs, equipment failure modes) to act as virtual experts in process industries.
Focus on high-impact problems—not trendy use cases—to drive real ROI and adoption of AI in industrial operations.
The future of AI lies in vertical-specific agents (not chatbots), with explosive growth expected in industrial, software, and engineering applications.
Success requires a 'citizen champion' to demonstrate value and simplify workflows, not just technical deployment.
…and 3 more takeaways available in PodZeus
Introducing Uptime AI and Its Mission
Sam Humphreys welcomes Jag Yatu, founder and CEO of Uptime AI, to discuss the company’s mission to improve margins in process industries using AI agents. Yatu explains Uptime AI’s SaaS platform, which reduces complex operational decision-making from years to days.
Case Study: Compressor Failure Diagnosis in 1 Hour
“And that whole additional process there was compressed from, you know, them already spending like months trying to analyze it to a matter of, you know, one hour and they knew the answer.”
The Full Suite of Industrial AI Agents
Yatu details Uptime AI’s range of specialized agents: root cause, maintenance optimization, HAZOP safety, and process yield. These agents target the 15–20% O&M cost segment where the biggest margin improvements occur.
How Uptime AI’s Agents Are Trained with Domain Expertise
The company builds agents with embedded domain skills—like understanding PNIDs and equipment failure modes—rather than relying on generic models. These skills are reusable across industries and orchestrated like expert reasoning.
Driving AI Adoption in Industry: Practical Steps
“Make sure that when you start the engagement, you're picking like a citizen champion who is going to really take the application or take this technology and show it to everybody else how it's helping their life.”
“We won't be talking, the agents will be talking.”
“And that whole additional process there was compressed from, you know, them already spending like months trying to analyze it to a matter of, you know, one hour and they knew the answer.”
“Make sure that when you start the engagement, you're picking like a citizen champion who is going to really take the application or take this technology and show it to everybody else how it's helping their life.”
Host
Guest
jag yatu
person
uptime ai
organization
cira week 2026
other
petrochemical plant
other
mitsubishi
organization
compressor failure
other
westbridge capital
organization
yokogawa
organization
abb
organization
s&p global energy
organization
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