AI That Survives (And Thrives) During
Scenarios: a total comms blackout, GPS jamming and spoofing, a nation-state cyber attack, contested, denied spectrum, a coronal mass ejection, an orbital debris cascade, electronic warfare, a poisoned-data attack, a severed uplink, a geomagnetic storm, and a supernova.
A working platform with a swappable brain. It runs on your hardware, inside your perimeter, with nothing leaving the building. Hardened for jamming, intrusion, blackout, and whatever the sun decides to do next.
Space Systems Command · Introduced by Tony Swantek
Three properties, decided before the first line of code.
Every choice in this architecture traces back to one of these. They are not features that got added. They are the reason the thing is shaped the way it is.
Resilient
Degraded, denied, disconnected. The system assumes all three are the normal case, not the exception. No external dependency sits in the critical path.
Private
Data stays inside the perimeter. No identifiers in the payload, no telemetry leaving, no third party holding a copy of what your people asked.
Intelligent across systems
The value is not one answer. It is one grounded picture, assembled from sources that never talked to each other, cited back to what your unit already wrote.
Speed only counts if the call is right, and only if the tool is still standing at the moment it is needed. Everything here is built to that second half.
A live platform, in production, with real users on it.
Not a prototype, and not a pitch to buy a subscription. What matters is how it is built, because that is what makes it portable into your environment.
Chat assistant
A conversational surface operators already understand, grounded in the organization's own material rather than the open internet.
Knowledge base
A curated, permissioned source of truth. Answers come from it, and the answer shows what it came from.
Document search
Bulk processing and retrieval across large document sets, so a question about policy returns the policy, with the citation attached.
Permissions & admin
Role-based access, user management, and an administrative layer built for a real organization rather than a demo account.
Workflow automation
Scheduled and triggered jobs running against the same AI layer without a human in the loop, on the same permissions model.
One AI adapter
Every model call routes through a single integration point. The model is an address the system points at, not a dependency baked through the code.
The brain is an endpoint, so it comes out.
Every provider runs through one adapter. Pointing the platform at a model on your hardware is a small, checkable change, not a rebuild. Model selection stays a deployment decision, which means we build to your approved list instead of arriving with a favorite.
If provenance matters, and we assume it does, there are options that publish training data and not just weights. That is your call to make, and the architecture is built so it stays your call.
Hardened for cyber attacks, supernovas, and everything in between.
The threat list looks wildly different top to bottom. The engineering answer is the same every time: nothing outside the room is allowed to be load-bearing.
Give us a week and we will show it answering from its knowledge base with the network physically disconnected. Live app, cable pulled, still working.
Private by construction, not by policy.
A privacy promise you have to trust is worth less than an architecture where the data physically has nowhere else to go. We build the second kind.
Inference stays on your metal
Models are served from hardware in your environment. There is no request that crosses a boundary, which means there is no request anyone else can log, retain, or subpoena.
Anonymous in the payload
In the platform running today, model calls carry no IP address and no user identifiers. The only user data present is the context deliberately injected to answer the question. Verified against the code, not assumed.
Transcription never leaves either
Speech-to-text runs on the same local hardware. Audio from a briefing, a call, or a console session is processed in the building and stays there.
The commercial exhaust comes out
Billing, marketing integrations, analytics, external email. None of it belongs in a government build. Removing it shrinks the attack surface and the data-handling story at the same time.
One picture, pulled across systems that never talked.
The hard part was never generating text. It is getting the right material in front of the model, with the right permissions attached, and delivering the result where the work already happens.
Every source
Policy documents, training material, tickets, transcripts, schedules, whatever the unit already produced and cannot find.
At the record
Access rules travel with the content, so an answer can never surface something the person asking is not cleared to see.
Across the seams
Retrieval spans all of it at once. The value shows up in the seams between systems, which is exactly where a person loses hours.
Cited, and scored
The answer shows its source and states how sure it is, so a Guardian can check the claim in one click instead of taking it on faith.
Into the workflow
Output lands inside the process that already exists. A new screen to monitor is a new burden, and that is a failed tool.
Not a chatbot bolted onto a wiki. One brain reading everything the organization already wrote, and answering from it.
Anything we build follows three rules.
Human-AI teaming, not human replacement. The AI eats the firehose. The human makes the call.
Less on the operator's plate
If a tool adds a screen someone has to read, it made the job worse. Output arrives inside the workflow that already exists, or it does not ship.
Honest confidence
The system states how sure it is, and that number has to be true. A tool that says ninety-five percent and is wrong a third of the time is worse than no tool, because now the human trusts it.
The model is a target
Poisoned data, spoofed feeds, prompt injection. We design assuming someone is attacking the AI itself, because eventually someone will be.
What we could build for the lab.
Custom builds inside your environment, in the family of tools Space Systems Command has already funded and already said it needs.
Knowledge assistants for units without one
Policy, training, benefits, and jargon answered from your own documents, with the source shown every time.
Admin & documentation automation
Built to the standard that actually matters: the person does not have to go back and double-check the output.
Contract & proposal analysis
Digging through large paperwork sets and surfacing what matters, with stated confidence, for a contracting staff stretched thin.
Interfaces that show their certainty
Screens that carry an honest confidence signal, not just an answer, so the operator trusts the tool the right amount in both directions.
NOT OUR LANE // orbital tracking, sensor fusion, or anything requiring a cleared facility.
What stands between today and a government deployment.
Three pieces of real work. Naming them here is the point, because a vendor who only lists upsides is a vendor you have already met.
Document search needs a local model
That piece currently calls a cloud service. Swapping in a local one is solved work, but it means re-processing the documents. A week, not a footnote.
The database layer must be self-hosted
Built on an open-source stack that supports exactly this, so it is a supported path rather than a science project. Still real work, and the largest item on the list.
Everything commercial comes out
Billing, marketing integrations, external email. Stripping it reduces the attack surface and shortens the accreditation story.
Two more we will say before you have to ask. It runs in your cloud or on your hardware, never ours. And we would not be the prime. Realistically that is a prototype agreement or a build under someone already on contract, and pretending otherwise would be the fastest way to waste your time.
How we would work with you.
Your environment, your rules
Your cloud or your hardware, your approved model list, your provenance bar. Because model selection is a deployment decision in this architecture, we build to your constraints instead of arriving with a favorite.
A written spec, tested against
Custom means a requirements document the build gets verified against. We do not agree to scope on a call. We agree to write one, and then we get held to it.
Through the right vehicle
An existing contract vehicle, a prototype agreement, or building under a prime already on contract. Whichever one you tell us is real.
The short version: a small team that already ships production AI, already runs its own models on its own hardware, and already has most of the thing built.
Two people. Production AI, already in the field.
We build robust, cutting-edge AI systems that have to survive contact with a real environment, not a demo. The model layer is the last decision, not the first.
Kim Garst
Builds and runs production AI products with real users on them. Owns the relationship, the requirements, and the question that actually matters: does the operator use it, or does it sit on a slide.
Matt Johnston
Ships the systems end to end, no agency overhead. Already running local inference and transcription on his own hardware, daily, which is why disconnected is a working posture instead of a future promise.
Ship the hard part first
Interface, knowledge, permissions, workflows. A year of production work, already done, already used. The AI brain is an endpoint we point at whatever you approve.
Build as if it will be attacked
Poisoned data, severed uplink, jammed spectrum. Nothing outside the room is load-bearing, and commercial exhaust never enters the government build.
Stay small on purpose
No agency layers, no account team between you and the people writing the code. A written spec, then we get held to it.
Introduced by Tony Swantek. If this leaves the room, those are the two names attached to it.
Twenty minutes on the workflow eating the most Guardian hours.
We are not here to demo a product. We are here to find out what is actually broken, and whether it is the kind of thing we can build.