First, a truth
With cloud AI, every prompt leaves the building.
The moment your team types a question into a cloud-hosted assistant, your thinking becomes traffic — routed to a data centre you don't own, on terms you didn't write.
Your AI. Your data. Nobody else's cloud. A 120-billion-parameter class model that runs on processors you already own.
First, a truth
The moment your team types a question into a cloud-hosted assistant, your thinking becomes traffic — routed to a data centre you don't own, on terms you didn't write.
And it isn't free
Every answer carries a usage charge. Every fine-tune can expose valuable intellectual property. It is the only bill in your company that goes up when your people get better at their jobs.
Then, a line
One rule, and everything else follows from it: the model comes to the data. The data never goes to the model.
And when we were done
So we did the only responsible thing.
We unplugged it.
The unplug test
It arrives about forty minutes in, usually from the quietest person in the room: what happens if I pull the cable?
So ask us to pull it during your demonstration. The conversation carries on. That is the whole product, in one gesture.
Illustrative sequence. Ask us to perform the physical test during your demonstration.
Technology built. Deployed now.
The breakthrough is no longer a laboratory claim. It is working across banking, healthcare, aerospace, retail, genomics, IT and education.
Eight live deployments. Names are under NDA and available on request.
Three commercial engines. One architecture.
Superchat moves the same local intelligence from enterprise compute to the point of action. The products stop being separate experiments; they become three commercial expressions of one architecture.
Your data
Your prompts, your documents, your source code, your customers' records — all of it stays inside the perimeter. Not encrypted in transit to someone else. Not in transit at all.
Your infrastructure
Private AI no longer begins with specialised accelerators, a new facility and the power and cooling to sustain both. It begins with processors your organisation can already operate.
Your continuity
Once a day, a licence check confirms your licence and AMC status. That is the only call we make, it carries nothing of yours, and no answer ever waits on it. Beyond that there is no model quietly deprecated from under you and no kill switch on your floor.
Your architecture
Organisation, device or machine. The intelligence moves to where the data, the decision and the work already are.
The commercial consequence
Use the compute estate you already know how to buy, secure and operate. Superchat turns private AI from an infrastructure programme into a software deployment.
For every deployment, we size the CPU architecture against the GPU alternative across hardware, power, cooling, implementation, support and three-year total cost of ownership.
Genie · Enterprise Intelligence
Turn existing enterprise compute into private AI infrastructure. Air-gapped. CPU-first. Data stays inside.
Deploy it
Air-gapped hardware in your rack, or a single-tenant instance inside your cloud account.
Work with it
Private assistants and agents that can read internal knowledge and source without exporting either.
Embed it
Local speech, reasoning and customer assistance embedded into the systems people already use.
Try it yourself
No form, no sales call, no trial key. This is a live Genie deployment — open it and judge the experience for yourself.
Ask Genie anything… Open the demoThe demo is hosted by us so you can try it in one click — it is the only Genie that runs on our hardware rather than yours. Every deployment we sell runs inside your own perimeter, which is rather the point.
Edge · Embedded Intelligence
Genie and Orb capabilities embed into devices, browsers, enterprise systems, vehicles and equipment — close to the decision, even when the network is absent.
Text, voice and vision stay local. The product gains intelligence without becoming a thin client for somebody else's data centre.
Once intelligence no longer depends on a data centre,
it can live inside a machine.
Swayam · Physical Intelligence
In development · started April 2026
Take the same local intelligence architecture into machines. Swayam reasons, sees and acts inside robots and autonomous systems. Every balance decision, every step and every route is computed on the machine itself. No cloud. No teleoperation.
Early prototype
Mechanical design in progress
Live prototype flying
Where it has to work
Three rooms. In every one of them, the reason to keep the data inside the building has a face.
03:04 · Intensive care
Hospital notes are the most personal data an institution will ever hold. Genie reads them, summarises them and answers questions about them without a single byte crossing the hospital boundary.
Live · A GCC healthcare group
09:41 · Incident desk
A bank cannot describe a live risk event to a third-party model in order to understand it. The monitoring, the correlation and the reasoning all run on the bank's own machines.
Live · A global investment bank
14:20 · Assembly floor
Twenty years of geometry, tolerances and failure history in one model. Predictive maintenance is worth a great deal — and worth nothing if the price of it is uploading the design.
Live · A US aerospace leader
Superchat Research · Kochi
CPU-native inference, conditional computation and speculative decoding are already in production. The research programme now makes that deployed advantage faster, smaller and harder to reproduce.
The same work extends local intelligence from the enterprise into devices and embodied control — without changing the rule that the data and the decision stay at the point of action.
The origin
The advice was consistent. You need a data centre. You need eight figures. You need to be in California.
Our founder had a room, one backer, and a stubborn suspicion that everybody had confused how it was being done with how it had to be done. Two decades of shipping first-in-the-world AI stood behind that suspicion — enterprise AI, industrial automation, aerospace robotics — and twelve months later the fourth attempt was the one that ran.
That first chapter answered whether it could be built. The answer was yes. The next chapter is scaling that architecture through three commercial engines: Enterprise Intelligence, Embedded Intelligence and Physical Intelligence.
You will not need to trust us on any of this. Ask for the box. Pull the cable.