The reliability intelligence layer between Physical Asset and Enterprise AI

The Industrial Outcome Intelligence Engine.

PlantOS™ tells your operators exactly what to fix before it breaks, then proves the fix worked.

Prediction ≠ Outcomes.

See AI Shields in Action Explore PlantOS™

1000

Plants Digitalized
Globally

167,837

Hrs. of Unplanned Downtime Saved

up to

99%

Prescriptions Acted
Upon

up to

10%

Less Maintenance Cost

up to

Less Conversion Cost

up to

2.5%

More Throughput

*Note – Data as of August 06, 2026 Source – PlantOS™ Digital Reporting System – User-validated True Positives & False Negative Rate

PlantOS™ is Infinite Uptime's Prescriptive AI Platform for heavy manufacturing, delivered as Production Outcomes as a Service. Where predictive tools warn that equipment may fail, PlantOS™ tells operators which fault to fix, why, and by when. Operators validate whether the prescription worked, and that feedback sharpens the next one. It turns equipment and process data into validated production outcomes: less unplanned downtime, lower maintenance cost, and higher throughput.

VERTICAL AI FOR OUTCOMES

Deep domain AI on critical assets, flexible coverage everywhere else.

Infinite Uptime's PlantOS™ applies equipment-specific AI to the assets that can stop production, and scalable wired or wireless coverage to everything else. A single risk model underneath turns all of it into maintenance, spares and CAPEX decisions.

01 · The Active Defense

AI Shields

Equipment-specific AI on the machines that can stop production. Each Shield is trained on one asset type, so it tells a mechanical fault apart from a process upset instead of flagging both as noise.

Mechanical AI Shields on Crane, Run-Out Table, and more
Mechanical plus process AI Shields on Kiln, Filler, and more
Dynamic FMEA with 24x7 human-in-the-loop CoE review

Explore AI Shields

02 · The Foundation

Flex Reliability

Coverage for the rest of the plant, sized to what each asset is worth. Wired continuous monitoring where a stoppage still costs money, wireless periodic monitoring where a scheduled health check is enough.

Wired coverage using piezoelectric and MEMS sensing technology
Wireless MEMS, with self-powered tags where cabling is impractical
Existing third-party sensor data ingested, no rip and replace

Explore Flex Reliability

03 · The Orchestration Layer

Plant Fusion

Infinite Uptime's PlantOS™ ranks what to maintain, stock and replace by risk. Scope escalates from asset to equipment, process, plant and fleet, and every job an operator closes returns as a label that sharpens the next decision.

RBI, RCM and FMEA applied to every failure mode
Open API and MCP carrying prescriptions into enterprise systems
Validated outcomes returned as labels that sharpen the fleet

See Plant Fusion

Client Testimonials

Our Customers Speak

Alec Glenn VP, Reliability JSW Steel, USA

Mr. Rajneesh Ojha Fibres Global MTC Lead Indorama Ventures

Mr. Carlos Francisco Guzman Banbury Mixers Maintenance Supervisors Tornel Tyres

Mr. Ashish Chandra Plant President JSW Steel (Dolvi)

Mr. Carmelo Rodriguez Production Manager Silgan Whitecap

Mr. Gaurang Kamat Engineering & Maintenance Head Vedanta Sesa Goa

Mr. Amit Khanna Vice President Business Excellence Tata Steel, Thailand

Mr. Ramesh Dham Digital Manufacturing Head Coromandel International

PlantOS™ is rated 4.5 out of 5 on Gartner Peer Insights.

PlantOS TM is rated 4.5 out of 5 on Gartner Peer Insights.

Trusted by the world's heavy industry leaders

Where Predictive AI Stops

What is the difference between equipment
failure and process-induced failure?

Equipment-Borne

Degradation from the inside

Mechanical faults that develop within the equipment itself over time.

20+ specific modes

Bearing wear

Unbalance

Misalignment

Looseness

Cavitation

Resonance

Lubrication degradation

Gear-mesh anomalies

The PlantOS™ Difference

Generic AI stops at the mechanical signature.

Vertical AI contextualizes both — improving prediction coverage, accuracy, and explainability.

Process-Induced

Stress from the outside

Operating conditions that accelerate equipment degradation.

20+ specific modes

Kiln ring formation

Thermal overstress

Cyclone coating buildup

Ladle heat profile drift

Hot-strip thermal fatigue

Wet-end web tension drift

Coupling thermal loads

Roll thermal overload

The Core Engine

The 99% Trust Loop

🎯

Accuracy

Model output

🤝

Trust

Operator belief

⚡

Action

Work order taken

📋

Feedback

Outcome captured

🏷️

Tagged data

Labelled signal

🚀

Better models

↻ feeds back

↻ loops back to Accuracy

Each loop makes the next prescription sharper.

The Trust Loop is how PlantOS™ keeps improving. Accurate prescriptions earn operator trust. Trust drives action on the plant floor. Each action produces a validated outcome, and that feedback trains better models. Better models raise accuracy again. Every turn of the loop makes the next prescription sharper and the whole system more trustworthy over time.

01 · THE FLYWHEEL

PlantOS™ industrial AI adoption paradox showing how low-accuracy prescriptions create operator distrust, reduce maintenance action and feedback, and cause AI model accuracy to stagnate or deteriorate over time.

01 / 04

IMPLEMENTATION

How long does it take to
deploy PlantOS™ Prescriptive AI?

The Path to Reliability Outcomes Your Operators Trust - in 90 Days

No rip-and-replace — works with your existing systems. First prescription in 2 weeks.
Scale with confidence.

Week 1-2

Solution Deployment

100% equipment coverage Day 1
Rotating + static equipment + process context
Baseline assessment complete

Week 3-4

First Prescription

Operator validation workshop
Digital signoff trained
First fault prescribed

Month 2

Scale & Optimize

Additional equipment lines
Process efficiency modules
KPI baseline established

Month 3

Plant-Wide

Board-ready ROI report
Expansion planning
99% Trust Loop complete

Ready to see your first prescription?

Book a discovery call. We'll model your specific equipment risk and ROI before you commit.

Try PlantOS™

Customer Proof

Operator Validated Outcomes

Validated on site and signed off by the operators who run the plant.

Steel India and USA

JSW Steel rolled PlantOS™ out across 139 plants in India and the USA and cut unplanned downtime 2X in under a year.

Read the JSW Steel story

Chemicals USA and APAC

Across 14 plants, Indorama Ventures caught developing equipment faults early with PlantOS™ and cleared them during planned shutdowns instead of forced ones.

Read the Indorama Ventures story

Tire Manufacturing Mexico

JK Tornel acted on PlantOS™ vibration alerts on its Banbury mixer line early enough to schedule repairs instead of absorbing a line stoppage.

Read the JK Tornel story

Mining & Metals India

Vedanta Group used PlantOS™ to intervene on failing assets before they stopped production, converting avoided breakdowns into recovered output.

Read the Vedanta Group story

Cement Saudi Arabia

SPCC replaced reactive firefighting with a daily prioritized work order queue from PlantOS™ and fixed critical assets before they failed.

Read the SPCC story

Chemicals and Fertilizer India

With PlantOS™ live across 27 plants, Coromandel International planned maintenance around real asset health and took equipment down on its own schedule, not the failure's.

Read the Coromandel International story

All figures validated by Customer's Reliability & Operations teams via PlantOS™ Prescription Engine

View All Case Studies

VERTICAL AI FOR OUTCOMES

Frequently Asked Questions

Explore common questions about PlantOS™, Prescriptive AI, equipment reliability, and operator-validated outcomes. Learn how Vertical AI helps heavy manufacturers prevent downtime and improve production performance.

01 What is prescriptive maintenance?

Prescriptive maintenance is the step beyond predictive maintenance. Instead of only forecasting that a machine / equipment may fail, it tells the maintenance team exactly which fault to act on, why it is happening, and what to do about it. PlantOS™ delivers this as a specific, validated instruction in a work-order prescription that an operator can act on immediately.

02 How is prescriptive maintenance different from predictive maintenance?

Predictive maintenance warns that equipment is likely to fail and roughly when. Prescriptive maintenance goes further and prescribes the exact corrective action, ranked by urgency and impact. PlantOS™ also captures whether each fix worked, so its recommendations become more accurate over time.

03 What is PlantOS™?

PlantOS™ is Infinite Uptime's prescriptive AI platform for heavy manufacturing, delivered as Production Outcomes as a Service. It reads both mechanical fault signatures and process-induced fault signatures to detect anomalies early, then issues clear prescriptions that tell operators what to fix, why, and by when. It is deployed across 1000 plants in 28 countries.

04 Which industries does Infinite Uptime serve?

Infinite Uptime works across heavy manufacturing, including steel, cement, mining, paper and pulp, chemicals and fertiliser, tyre and rubber, food and beverage, pharmaceuticals, and energy and oil and gas. Its Prescriptive AI is tuned to the specific failure modes of each industry's critical equipment, standard rotating equipment, and balance of plant equipment – thus ensuring full plant coverage.

05 How quickly does PlantOS™ deliver results?

Most sites receive their first prescription within about two weeks of installation. Full validated outcomes, such as measurable reductions in unplanned downtime, typically follow within the first two to three months as the system learns each plant's equipment and process conditions.

06 How does PlantOS™ avoid false alarms?

Every prescription is validated by the operators who act on it. That sign-off confirms whether the recommended fix was correct, and the feedback trains the models to be more accurate. The result is a high rate of user-validated true positives rather than generic alerts.

07 What return on investment (ROI) do customers see?

Customers use PlantOS™ to reduce unplanned downtime, lower maintenance cost by up to 10 percent, and raise throughput by up to 2.5 percent. Because a single prevented outage can offset the cost of the platform, most deployments pay for themselves early.

The Industrial Outcome Intelligence Engine.