Industrial AI · Consulting & Builds · Amman, Jordan
AI, put to work inside industrial operations.
Otoniq helps OT companies (plants, utilities, system integrators, machine builders) bring AI into their workflows, operations, and business. It's led by an industrial engineer who builds AI and lives on the plant floor, so the work starts from how a plant actually runs.
The problem
AI keeps stopping at the office door
Every industry is finding uses for AI. In OT the gap is different: the tools don't understand the work, and the people selling them have never done it.
AI is everywhere except the plant floor
Vendors demo chatbots and copilots for everyone else. Nothing on offer understands your PLC programs, your naming conventions, or your safety constraints.
Generic AI consultants don't speak OT
They've never read an electrical submittal, never carried a commissioning deadline, never explained to an operator why the line stopped. Their advice starts from software, not from your operation.
Your engineers don't have time to evaluate AI
Their day job is keeping lines running, not benchmarking models. So the question of where AI fits stays unanswered, quarter after quarter.
The knowledge problem underneath it all
Documentation scattered across drives and inboxes, veterans retiring, tribal knowledge walking out the door. Any serious use of AI runs into this first.
What we do
Consulting and builds, from one team
Three ways we put AI to work in OT companies. Each starts small, ships something concrete, and is judged by your engineers.
AI opportunity mapping
An engineer's assessment of where AI actually pays in your workflows, operations, and business, and where it doesn't. You get a map you can act on rather than a slide deck.
Learn more →Custom AI systems, built and integrated
Document-grounded assistants and agent workflows wired into your real systems: your documentation, your data, your network. Deployable on-premise by default.
Learn more →Engineering workflow automation
PLC documentation, submittal and report processing, the repetitive engineering work nobody has time for. It gets automated, and your engineers review the output.
Learn more →Flagship build
The kind of thing we build: your plant's knowledge, searchable at 2am
Our flagship system turns PLC programs, submittals, manuals, and commissioning reports into an assistant your engineers can question in plain language. It answers the way a careful engineer would. It's also the clearest picture of how we work.
Pump P-102 trips on overload a few seconds after start. Where do I start?
Check the soft-starter ramp time first. The commissioning notes flag that P-102's ramp was extended to 8 s after repeated overload trips during startup — a reset to factory defaults reproduces exactly this fault.
If the ramp checks out, verify the discharge valve interlock in FC_312: the start sequence expects MV-104 open to 30% before the run command is released.
What torque should the coupling bolts on P-102 be tightened to?
That's not in your documentation. The O&M manual covers alignment tolerances but doesn't list coupling bolt torque values. I don't guess — add the mechanical datasheet and ask again.
▸ Refuses when your documents are silent — no invented answers.
Illustrative exchange. Document names and tags are synthetic.
Every answer cites its source
Each response points to the exact document and section it came from: a submittal revision, a PLC routine, a manual page. Your engineers verify before they act.
It refuses instead of guessing
When your documents are silent, it says so and tells you what's missing. It won't invent a torque value or guess a setpoint.
It runs on your own documentation
Your tags, your naming, your equipment. It's deployed inside your network, not on the open internet.
The process
How an engagement works
Four steps from first call to a decision you can defend. There's no commitment until you've seen results on your own data.
01
Discovery call
Thirty minutes on your operation and where AI might actually pay. There's no pitch deck.
02
Scoped assessment or pilot
A bounded first engagement with a concrete deliverable: an opportunity map or a working pilot, not an open-ended retainer.
03
Build and integrate
We build the system on your real data, and your engineers judge it against what they already know.
04
You decide
Scale it, keep it as-is, or walk away with an honest map of what AI can and can't do for your operation. The choice is yours either way.
The founder
Run by an engineer who lives in both worlds
Otoniq is run by an industrial engineer who spends his days inside a working automation firm, around real plants, real panels, and real commissioning deadlines, and who builds AI systems. That's why the advice starts from OT reality: what gets recommended is what would survive on an actual plant floor.
Meet the founder →FAQ
Questions OT teams ask
The ones that come up in almost every first conversation.
We don't know where AI fits our operations. Is that a problem?
It's the normal starting point. Mapping AI against your actual workflows is exactly what the first engagement does. You get an honest map of where AI pays, including where it isn't worth it.
Do you understand OT constraints like legacy systems, safety, and air-gapped networks?
Yes. Otoniq is run by an industrial engineer who works on real control systems. On-premise deployment inside your network is the default, and nothing we build is designed to touch a safety function.
Can you work with our existing systems, like Siemens, Rockwell, SCADA, and historians?
That's home turf. Work starts from your PLC programs, documentation, and data as they are, not from a rip-and-replace.
Do you consult, or do you build?
Both. Engagements usually start with mapping and end with a working system. The plant knowledge assistant is the flagship example of what that looks like.
Where does our data go?
Systems run on your own documentation and data. On-premise is the default: your documents don't leave your site, and nothing is used to train public models.
What does an engagement cost?
Scope comes first. Everything starts with a free discovery call and a bounded first step with a concrete deliverable, and there are no open-ended retainers.
Find out where AI actually pays in your operation
One discovery call is enough to tell whether there's a first project worth doing, and what it would look like.
Book a discovery callContact
Prefer email? Tell us about your operation.
A few lines on what you run and where the friction is today is plenty. You'll get an honest read on whether AI fits, and where to start if it does.
Email Us
malek@otoniqai.comRather talk it through?
Book a 30-minute discovery call about your operation and your systems. There's no pitch deck.
Book a discovery call