See what every machine is doing, and what to fix before it breaks. Every alert comes with instructions the shop floor can act on.
Every line, machine and shift on one screen, then the analytics to ask why. OEE trends, quality drift, energy per unit, cost per batch: each one is an answer your team can act on.
Fleet-level totals, line-level drill-downs and asset-level twins. Every view is role-based and configurable by people who do not write code.
Six properties rather than six features. Three sit in the platform: OEM semantics, OPC-UA connectivity and explainable alarms. Three sit in delivery: the closed loop, site templates, and where your data lives.
Native understanding of equipment families, failure modes, process flows and OEM telemetry semantics. None of it comes from a generic template.
Rapid, repeatable factory connectivity for common PLCs. Vendor-agnostic, industrial-grade data standard.
Physics priors plus ML produce explainable alarms engineers trust. False positives stay near zero.
Alerts become work orders. Work orders find the right technician with the right parts. Fixes update the twin.
Line presets and pre-trained models for common equipment, so a site comes up in weeks.
SaaS, a private AI instance, or an on-prem gateway. You own your data and you can take it with you.
| HUMAN-OPS CAPABILITY | REDZONE | FIIX | MVP ONE | OUR PLATFORM |
|---|---|---|---|---|
| Operations daily mgmt | ||||
| Equipment ticketing | ||||
| Work orders + PM | ||||
| Spares visibility | ||||
| Purchasing (PR → PO) | ||||
| Vendor mgmt on assets | ||||
| Quality / compliance | ||||
| Skills / training | ||||
| Physics-assisted ML | ||||
| Digital twin + CMMS loop | ||||
| OPC-UA native ingestion | ||||
| COVERAGE INDEX · MAX 33 | 19 | 18 | 21 | 33 |
A multinational OEM partnered with us to unify equipment connectivity, CMMS and AI across end-to-end bakery lines, from mixer to packer. The goal was a single non-siloed view where production, maintenance, quality and procurement decisions share one causal timeline.
Oven belt failures used to waste full batches. Now PAHAG catches bearing wear two shifts early, the twin generates a work order, parts reserve automatically, and a qualified technician arrives at changeover. Zero lost batch.
Scope is decided by telemetry depth, automation density, and whether uptime is a KPI someone already owns. Five profiles are in. Five are out, and we say so before you buy.
Five objections come up in almost every deal. They are recorded here in the customer's own words, with the answer we give in the room rather than the one we give after the contract.
Four engagement stages, from proof of concept to multi-site enterprise. Each has a fixed scope and a stated elapsed time.
Data onboarding + overlay on existing telemetry. Prove one KPI.
Predictive models on one line. Outcome-linked pricing.
Full four-pillar platform across a site. CMMS integrated.
Multi-site. Standardized KPIs. Private AI or on-prem options.
Every operation in the world, whether factory, building or field, runs with the intelligence of its best day, every day.
Any machine, device or building streaming data the same week you sign.
AI-powered operations assistants that turn telemetry into decisions people trust.
Every deployment makes the platform smarter for every customer.
A 30-minute call with a solutions engineer. No pitch deck, just your lines on a whiteboard.
