The operating system for manufacturing. Connects your machines. Runs your plant. Learns from every shift.
LoomOS connects any machine in minutes, learns each machine's normal, catches defects on camera and runs operations end to end, on your own server.
- CNC-07vib 4.2 mm/s● Watch
- Robot cell 238s cycle● Running
- Press line 196 strokes/min● Running
- Paint boothchangeover● Idle
CNC-07 vibration is 18% above its 7-day baseline. Maintenance work order raised.
Your machines already report everything. Nobody is listening.
Every machine on your floor produces speed, temperature, vibration, current draw and counts, every second of every shift. Almost none of it is captured. What gets recorded is what someone writes on a batch card and types into Excel two days later.
Orders, BOMs, inventory. Clean, structured, board-level visibility.
Paper batch cards, WhatsApp groups, Excel trackers. Dozens of people walking the floor. Guesswork.
Speeds, temperature, vibration, counts. Generated every second, seen by no one.
- US$0.5–2M+
- Typical cost of a traditional MES per plant
- 12–24 months
- To deploy, mostly consultants writing custom code
- 80% services
- Legacy MES is a project you commission, not a product you buy
MES was built to record. LoomOS is built to learn.
Every MES stores what happened. LoomOS understands what is happening, because it was built on data and AI from day one.
Machines at the bottom, sales order at the top. Traceability, roles and audit run through all four.
- A database with workflows, every rule hand-coded by consultants
- AI features bolted on later, sold as separate modules
- Tells you yesterday's OEE in a report nobody reads
- Every new plant is a new services project
- Learns each machine's normal: 7 days of telemetry becomes a live baseline that flags bearing wear before it becomes downtime.
- Judges every unit, not a sample: Your own images train the inspection model, fused with live sensor readings.
- Answers in plain language: Ask why Line 2 quality dropped at 3pm, against live plant data.
- Compounds: Every shift of data makes the models better, and the moat deeper.
4M traceability
Man, machine, material, method
Roles and access
Everyone logs in as themselves
Audit trail
Every change, who and when
Five studios. Five questions.
Each studio answers a question somebody in the plant already asks every day. All five run on the same server, on the same data, with no separate integration and no second vendor.
What is about to fail?
Health models for VMC, HMC, turning, grinding, presses, moulding, welding robots, compressors and furnaces. Baselines per recipe, drift flagged before failure.
- Ships knowing, then learns yours
Is this part good?
Camera images, IMTE gauge readings and live process data fuse into one decision, with a confidence score and which of the three drove the call.
What should happen now?
Raises the maintenance work order, escalates when quality drops, notifies the right person. The operator decides, and every decision is logged.
Why did that happen?
Ask the plant a question in plain language across telemetry, orders, quality and traceability. Point it at your CCTV and ask about video the same way.
What if we changed it?
Built from your routings, cycle times and changeovers. Add a machine or a shift, resequence, change batch size. Throughput, utilisation, bottleneck and WIP come back.
The foundation
All five studios run on the same server as the rest of the platform. Models train per machine and per recipe, and inspection can start from twenty good-part photos, so nothing waits on a dataset you do not have.
Compounding
Quality decisions fuse camera, measurement and sensor evidence, and report which of the three drove the call. Start with visibility, turn on the rest at your pace, nothing gets re-implemented later.
One system, from the machine to the sales order.
Four layers, stacked from the machine upward. Pick the protocol from the connector catalogue, point it at the machine, map the tags in the interface. Read-only until you decide otherwise.
“Five studios, one data, on when ready.”
Predict, inspect, act, answer, simulate
- Predict, inspect, act, answer, simulate — one server
- 4M traceability, forward and backward
- PPE and zone watch on existing cameras
- Smart glasses worker, Hindi or English
“A commercial layer, if you lack one.”
Catalogue, materials, inventory, orders, dispatch
“Runs the shift, however you run it.”
Shops, shifts, work orders, recipes, OEE, maintenance
“Old machines and new. No SOW.”
PLCs, CNCs, cameras, gauges, sensors, SCADA
We don't demo slides. We carry a working factory into the room.
Plant-in-a-Box: a live motor with sensors, a conveyor with a camera, and the full LoomOS stack. End to end, in 25 minutes.
- 01
An order arrives
A work order is created. The motor starts at recipe speed. Nobody typed anything.
- 02
The plant goes live
Telemetry streams every second. OEE calculates in front of you.
- 03
Trouble, caught twice
The camera catches a marked defect. Coins taped to the shaft trigger a bearing-imbalance alert within thirty seconds.
- 04
The plant explains itself
Ask what happened. The order completes and the batch record writes itself.
LoomOS, answered.
Connect any machine in minutes.
Learn each machine's normal. Catch defects on camera. Run operations end-to-end, on your own server, on your terms.
- 100%
- Honest Pricing
- Superfast
- Executions
- 0%
- Vendor Bias
- Everything
- Tech | Data | AI