● AI-Powered Predictive Maintenance

BODHI: the AI engine for manufacturing reliability

BODHI is an AI-powered predictive maintenance platform for manufacturing plants that diagnoses equipment failures in plain language, predicts breakdowns before they happen, and automatically triggers the right corrective action. It's built for plant maintenance teams in the UAE and India.

DiagnoseRoot cause in seconds
PredictFailures before they happen
ActRight fix, automatically
BODHI predictive maintenance dashboard showing MTTR, MTBF, equipment at risk, and AI root cause diagnosis of a pump fault
What You Get

Tangible results on your plant floor, not another dashboard

BODHI isn't built to look good in a report. It's built to get your line back up faster, keep your best technician's know-how working every shift, and stop the same failure from happening twice.

60% Faster

Diagnose in Seconds, Not Hours

Technicians get root cause and next steps instantly. No more digging through manuals or waiting on the one person who "just knows."

Less Downtime

Wrenches Turn Sooner, Not Later

Only 30–40% of repair time is hands-on fixing. BODHI cuts the diagnosis overhead that eats the rest, so lines come back online faster.

Fewer Repeats

Catch It Long Before It Breaks

Anomalies are read against your own failure history, so problems get flagged and fixed right the first time, before they become breakdowns.

Nothing Lost

Your Best Technician, Every Shift

Capture the expertise that normally walks out the door at retirement, and make it available to every technician, on every shift.

Backed by independent research: AI-driven predictive maintenance cuts unplanned downtime by up to 45% and maintenance costs by up to 30%. (PwC, "An introduction to implementing AI in manufacturing")

The Cost of Guessing

Every hour spent diagnosing is an hour your line isn't running

Three maintenance strategies are common on plant floors today. None of them tell your technician what to actually do.

⚠️

Reactive Maintenance

Every failure starts from zero. Technicians troubleshoot blind, every single time, with no history to work from.

82% of asset failures happen at random (ARC Advisory Group)
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Condition-Based Monitoring

A threshold crossing isn't a diagnosis. It's a number with no explanation of what's actually wrong.

30–40% of repair time is spent actually fixing, not diagnosing
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Predictive Alerts

An anomaly flag isn't an answer. Your team still has to figure out the root cause from scratch.

$1.4T lost to downtime every year, worldwide (Siemens)
How BODHI Works

From symptom to solution, in one conversation

No new dashboards to learn. No black-box alerts. Just a straight line from "something's wrong" to "here's what to do," built on your own maintenance history.

Step 1: Live Today

Ask, and get the answer

Describe the symptom in plain language and get the root cause back in seconds, not a support ticket, not a manual search.

  • Diagnoses natural-language symptoms in seconds
  • Grounded in your own RCA records, manuals, SOPs, and spare parts data
  • Expert-level guidance, available to any technician, any shift
Step 2: Predictive Engine

Catch it before it breaks

BODHI watches live equipment data around the clock and flags trouble early, before it turns into a shutdown.

  • Monitors live equipment data continuously
  • Flags anomalies as they emerge, not after the fact
  • Every anomaly is read against your documented failure history
Step 3: Closed Loop

The right action, automatically

Detection doesn't dead-end at an alert nobody reads. It routes straight into diagnosis and action.

  • Anomalies are routed back for diagnosis automatically
  • The right corrective action is triggered, with no waiting on someone to notice
  • Detection plus reasoning means fewer false alarms
Higher MTBF Your machines run longer between failures
Lower MTTR Your technicians fix it faster, every time
Right Diagnosis At the right time, not just when the expert's on shift
BODHI dashboard showing an AI diagnostic conversation for Error Code 3500 on Agitator AGT-101, with likely causes and recommended actions
Why BODHI

Other tools stop at the alert. BODHI tells you what to do next.

Most tools in the market stop at one piece of the puzzle. BODHI closes the whole loop: from symptom, to cause, to fix.

Scroll sideways to compare →

Capability Enterprise Incumbents Asset Monitoring Tools Regional Services BODHI
AI root-cause diagnosis ✗ ✗ ✗ ✓
Predictive anomaly detection ✓ ✓ ~ ✓
Closed-loop corrective action ~ ✗ ✗ ✓
Built on your own maintenance history ~ ✗ ~ ✓
Accessible mid-market pricing ✗ ✓ ✓ ✓
No proprietary hardware required ~ ~ ✓ ✓
Live in Production

Running on a real manufacturing floor, right now

BODHI is deployed with ABT Group, an industrial services conglomerate, monitoring 100 assets and diagnosing equipment symptoms in live production today.

Cognition Layer
Live today, in production
Predictive Engine & Closed Loop
Live before January 2027
Technician on a plant floor holding a tablet with the BODHI app open, standing next to industrial pump equipment
FAQ

Common questions about BODHI

Straight answers, no sales spin.

What is BODHI?

BODHI is an AI maintenance engine built for manufacturing plants. It diagnoses equipment failures in plain language, predicts problems before they happen, and automatically triggers the right corrective action. Technicians get a working diagnosis in seconds instead of digging through manuals or waiting on the one person who "just knows."

How does BODHI diagnose equipment failures?

A technician describes the symptom in plain language, and BODHI returns the likely root cause and next steps in seconds. Every answer is grounded in the plant's own RCA records, manuals, SOPs, and spare parts data, not a generic knowledge base, so the guidance reflects how that specific plant's equipment actually fails.

How is BODHI different from condition-based monitoring or predictive alert tools?

Condition-based monitoring flags a threshold crossing. Predictive alert tools flag an anomaly. Neither tells a technician what's actually wrong or what to do next. BODHI closes that gap: it detects the anomaly, diagnoses the root cause against the plant's own failure history, and routes the right corrective action automatically, so detection turns into a fix instead of an alert nobody acts on.

How does BODHI reduce downtime and maintenance costs?

BODHI cuts the diagnosis overhead that eats most repair time. Since only 30 to 40 percent of repair time is spent actually fixing equipment, removing the guesswork gets lines back online faster and catches recurring failures before they repeat. Independent research from PwC found AI-driven predictive maintenance can cut unplanned downtime by up to 45 percent and maintenance costs by up to 30 percent, in line with the gains BODHI is built to deliver.

Does BODHI require new hardware or a new dashboard to learn?

No. BODHI works with a plant's existing equipment data, maintenance history, and documentation. There is no proprietary hardware to install and no new dashboard for technicians to learn, so it fits into how the floor already runs.

Does BODHI support manufacturers in the UAE and India?

Yes. BODHI is built for manufacturing plants in the UAE and India, with local contact points for both regions.

Get in Touch

See what BODHI could save your plant

Book a walkthrough and we'll show you how BODHI would diagnose your last few breakdowns, using your own manuals and incident history.

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Founder
Sunil Sandeep
📞
Contact No.
Request a Demo