AI Co-Workers built for the factory floor and the field.
Three places where manufacturers lose time, money, and customers every day — and how Subatomic’s AI Co-Workers close those gaps.
The right answer, before noon.
Your best technician is standing in a muddy yard next to a broken compact track loader. The customer is watching. The manual is 1,400 pages long. The average support call takes 47 minutes.
Marcus calls from the field.
Hydraulic fault on a compact track loader. He’s seen it before, but the procedure was updated last quarter and he can’t remember which revision is current.
AI co-worker searches everything.
Tablet app queries current docs, historical service cases, engineering change notices, and parts revisions — not just one manual, the full knowledge base.
Torque spec. Updated procedure. Parts number.
Four minutes from call to fix path. Marcus is done by 10:40 AM and on to the next job instead of waiting on hold.
The knowledge already exists. Your technicians just can’t find it fast enough. An AI co-worker that knows every manual, revision, and prior case turns a 47-minute phone call into a 4-minute lookup.
Knowledge that moves at the speed of product.
Engineering just pushed a hydraulic system update. Ninety days from now, 400 dealer contacts are supposed to be trained. Last rollout hit 60% completion. You don’t find out who missed it until warranty claims start coming in.
Engineering ships a change.
New hydraulic calibration procedure. The old training is now wrong. Somewhere across your dealer network, a tech is about to do it the old way.
AI co-worker sees the delta.
Change detection across modules fires automatically. Draft training content, field bulletins, and dealer notifications are generated from the actual engineering update — not a 90-day lag.
400+ contacts, tracked.
Notifications go out, completion is tracked per person, gaps are escalated automatically. You see who’s current and who isn’t — before warranty claims tell you.
Training isn’t a course you build once a year. It’s the delta between what engineering shipped this week and what your techs know today. Close that gap in days instead of quarters.
The data existed. The insight didn’t.
Three thousand machines in the field are sending telemetry right now. Somewhere in that stream is Machine #2847, throwing the same fault code for the sixth time in 30 days. Nobody’s connected the dots yet.
3,000 machines, always on.
Machine #2847 logs a fault at 6:14 AM. It’s one of tens of thousands of events that day — the kind of signal that used to drown in the noise.
Pattern recognition across the fleet.
The AI co-worker notices: this fault has fired six times in 30 days. Three of the matching patterns preceded downtime. A technician is already scheduled to be on-site Thursday.
Prevent the downtime. Pay for the year.
Unplanned downtime on this machine runs ~$5,000/day. One prevented failure pays for the deployment. The data was always there — the insight is what’s new.
You’re not missing telemetry. You’re missing analysis. Pattern recognition across a fleet of thousands is exactly what AI co-workers do better than any dashboard.
Deployed in your environment. On your terms.
Manufacturing data — engineering drawings, telematics streams, service histories, dealer records — is sensitive by default. Subatomic meets your security posture, not the other way around.
On-Premise
Deployed entirely inside your own data center. No data leaves your perimeter. Fully compatible with existing IT governance, identity providers, and audit requirements.
Private Cloud / VPC
Runs in your dedicated cloud tenancy — AWS, Azure, or GCP. Isolated infrastructure, your keys, your logs. All the benefits of cloud scale without shared tenancy.
Air-Gapped
For environments with strict separation requirements. Full offline deployment supported for sensitive engineering data, ITAR workflows, and regulated operations.
Stop wondering. Start hiring.
Your best technician already exists. Your best trainer already exists. Your best analyst already exists. We just built them to work alongside you.
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