AI Troubleshooting Copilot · Shop Floor

25 downtime events a month.
Your operators handle zero
without help.

Machine Mary guides operators through troubleshooting — step by step, grounded in your machines and your fault history. Every event becomes a record. Knowledge compounds. The plant gets smarter.

7 min
Avg. resolution with Mary
40–60 min
Without
24/7
Every shift, every line
Live · 02:14 AM Voice or text input
Tap a step to flip through the prototype
Before vs. After · same machine, two shifts

What an hour of downtime looks like — with Mary, and without.

The dramatic save matters. The routine save matters more — that's where the volume lives.

×
Before
Without Mary
VS
After
With Mary
Without Mary 2:14 AM · Tue
The 2 AM phone call.
Operator hears an unusual noise from Station 12. Tries restarting — no luck. Line leader takes a look — not sure either. They call maintenance at home. Tech drives in, asks "what happened?" Operator re-explains. Tech re-diagnoses from scratch, finds a material jam in the feed assembly. Clears it in 3 minutes.
Downtime · cumulative00:00 → 00:60
40–60min · no record
With Mary 2:14 AM · Tue
No phone call. 7 minutes.
Operator opens Mary, taps Station 12, records: "weird noise, machine stopped." Mary matches the pattern — two options: (A) check feed assembly for jam, (B) check drive belt tension. Operator taps A, clears the jam, line restarts.
Downtime · cumulative00:00 → 00:07
7min · fault logged
Without Mary 10:47 AM · Tue · routine
The error code nobody remembers.
Operator sees an error code on the HMI. Not sure what it means. Asks around — nobody's sure. Calls maintenance. 25 minutes pass. Tech comes, hits a reset sequence nobody on the line knew about. Same error Thursday. Same delay.
Downtime · cumulative00:00 → 00:30
30min · for a 2-min fix
With Mary 10:47 AM · Tue · routine
Knowledge that compounds.
"Getting error 14." Mary: "Sensor timeout. (A) Reset — hold START 3 sec then CLEAR, (B) Check proximity sensor on left rail." Operator taps A. Machine runs. Thursday, a different operator gets Error 14. Mary already knows.
Downtime · cumulative00:00 → 00:03
3min · added to knowledge base
These routine events happen 3–4× per week at a typical plant. Each one costs 20–45 minutes while the escalation chain runs. That's 8–12 hours of lost production a month — on problems that should've taken five minutes.
How it works

Four steps. Five seconds to scan.

QR code on the machine. Phone in the operator's pocket. No new dashboards, no training program, no IT project.

01 / Trigger
Machine acts up.
Alarm, unusual noise, bad parts, an unexpected stop.
02 / Open
Operator opens Mary.
QR scan or dropdown. Describe the problem by voice or text.
03 / Guide
Mary guides.
Tappable A/B/C options. Right things tried in the right order.
04 / Resolve
Resolved or escalated.
Fixed → logged. Not fixed → maintenance gets the full context.
The numbers

Why this is a $50 billion problem.

The math that gets a 30-minute call on the calendar.

Problem scale
25
downtime events per plant, per month
Source · Siemens, 2024
Knowledge crisis
2.8M
US manufacturing workers retiring by 2033
Source · Deloitte
Cost
$50B
lost annually to unplanned downtime in US manufacturing
Source · Fortune Business Insights
Mary's ROI
7–18×
return on every dollar spent on Mary
Source · Conservative internal model
Who's behind this

Built by repeat founders. 200K+ IoT deployed. One unicorn built. Now turning to manufacturing.

Co-founder · CEO
Aniket Deb
Built Bizongo — one of India's earliest B2B e-commerce unicorns. IIT Bombay. A decade of scaling complex B2B operations across manufacturing and supply chains.
Co-founder · CTO
Pushkar Limaye
Built Carnot Technologies — 200K+ IoT deployments, 7 patents, acquired by Mahindra & Mahindra. IIT Bombay. 11 years turning messy industrial data into systems that work.
Currently piloting with leading auto-component manufacturers.
Status · Active pilots · 2026
Book a call

See Mary in action.

30 minutes. We'll show you Mary on a real machine, walk through how it fits your plant, and answer questions. No pitch deck.

BringOne downtime story from your plant. We'll show you exactly how Mary would handle it.
Walk away withA clear picture of where Mary fits, ROI math for your plant size, and pilot terms if it's a fit.
Won't seeSlideware. Buzzwords. "AI-powered" anything.
Prefer email? pushkar@flosync.io
Pick a time · 30-min slot · Pacific / Eastern
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