Plant Cortex
An AI-powered operations platform for manufacturing plants — it answers questions straight from your own equipment manuals and data, every answer cited to the exact source, and it says so when it doesn't know instead of guessing. It also tracks the floor's daily paperwork: permits, near-misses, inventory, downtime, and shift handover, all in one place.
Every response points to the exact manual page it came from. If the manual doesn't cover it, it says so instead of inventing a plausible-sounding step.
Work permits and JSAs generated from the real, current procedure — a starting draft for your team to review and sign off, not an automatic approval.
Turn a written procedure into a visual step-by-step flow for training or a quick refresher on the floor.
Multilingual by default — a translated, cited answer beats a rushed on-the-spot translation of an English manual.
The floor doesn't just need answers — it needs a record. These used to live in spreadsheets, paper logs, or nobody's memory. Now they're tracked, with a real lifecycle and an audit trail.
Issue → active → closed, with a logged shift handover and role tracking. Nothing auto-closes — an unclosed permit past validity shows up as overdue instead of quietly disappearing.
A real structured report, routed to the right department, with photo evidence and an admin acknowledgement step so reports can't just vanish unread.
On-hand quantity and reorder points per part, with every adjustment logged as a movement — never a silent overwrite.
Every stoppage logged becomes real MTBF/MTTR/availability numbers per equipment, plus a trend and a top-offender chart — not just a list of incidents.
A running narrative for the whole shift, not just one permit — and the person writing the handover can't be the one who acknowledges it.
A tracked request from draft through received, with line items resolved back to a real source in your manuals — not a generated list you have to double-check.
This isn't a general chatbot with your PDF attached. It only ever answers from documents you provide, runs on infrastructure you control (yours or ours, your call), and every gap it can't answer gets logged for review instead of filled in with a guess. The same discipline applies to every AI-assisted view above: incident data is analyzed to spot patterns, never used to train or fine-tune the model, and every cited pattern is resolved back to a real record in your data before it's shown — never a paraphrase you have to take on faith.
We're taking on a small number of plants for a discounted pilot: one manual, one unit, 4–6 weeks, success criteria agreed before starting. No long-term commitment to see if it's useful for your team.
The core system and the registers above are live today. These are what we're building next, as we bring on early plants to shape them.
Today's purchase requests are tracked end to end but stand alone. Next: syncing that lifecycle with your existing ERP or procurement system, both directions.
Feed in your plant's past root-cause analyses, and the system surfaces probable causes for a new issue based on your own incident history — visible to your whole team, not locked in one person's head.
Safety permits generated in the exact layout your plant already uses and your team already trusts, not a generic template.
We've proven the engineering against a public test data source. Next is connecting it safely to a real plant's own historian — not live on any customer's equipment yet.
A 15-minute call, or a 90-second video first if that's easier.