The intelligence stays in the building.
Aspasia designs, installs, and maintains air-gapped AI systems for organizations whose data can't leave the premises — and advises honestly on the handful of tasks that can safely run somewhere else.
Organizations that keep their data in-house.
The same governance that keeps your records on your own metal is what rules out managed model services. You're least able to send data out — and stand to gain the most from intelligence that doesn't ask you to. We close that gap without opening yours.
Two things, done well: build the system, and tell you the truth about it.
The hardware and software, kept running.
We stand up the full on-premise stack — compute, models, and the experts that specialize them — and we keep it healthy. Maintenance isn't an add-on here. It's the relationship, and it's what you're paying us to own.
Where intelligence pays off, and where it shouldn't run on your metal.
Before any hardware, we review your operations and map where intelligent systems create real leverage. Part of that map is honest: which tasks, if any, can responsibly run as a managed service instead of in-house.
A compact model, sharpened by a library of experts.
Rather than one large model straining your hardware, we run a smaller open model and attach a mixture of LoRA experts (MoLE) — small adapters, each tuned for one task or department. The base stays fixed; the experts do the specializing.
- SpeedFaster responses on a smaller hardware footprint, with lower power draw.
- CostYou buy and run less compute for the same useful intelligence.
- TradeoffMore moving parts to tune and keep current — which is exactly the part we own.
Built to be trained, updated, and replaced — without touching your secrets or your uptime.
Trained on stand-ins, never your secrets
Each expert is built with LoRA fine-tuning and RLHF on data that mirrors the structure and context of your real work — without being your real work. Scrubbed, inert, or fully synthetic stand-ins: redacted or replica contracts in place of live matters, structurally identical records with the sensitive content removed. The expert learns the shape of the task; your data never enters our training loop.
Updates without the downtime
Because the experts learn from stand-ins, we can hold a faithful replica of your system on our own hardware. We fix, retune, or upgrade an expert there, validate it, then swap it into your live system in place. Adapters change; the system keeps answering. Near-zero downtime, by design.
Always current, never disruptive
Open models and adapter techniques move fast. We track the field and replace both the base model and the experts as stronger ones arrive. The system you run next year isn't the one you bought this year — and you won't feel the change while it happens.
It starts with a review, not a quote.
We don't lead with hardware. We lead with understanding what you actually need — and what you don't.
Assess
We map your operations, data-governance constraints, and where intelligent systems would genuinely pay off.
Specify
We spec a hardware-and-software build matched to those needs — and flag any work that can responsibly run as a managed service instead.
Provision
We provision and configure the system on your premises, air-gapped to your governance requirements.
Keep current
We keep models and experts tuned, patched, and replaced as the field moves. Ongoing — that's the relationship.
Not everything belongs on your own metal. Good counsel says so.
Some tasks touch nothing sensitive and run cheaper and better as a managed service. Others can never leave. We draw that line with you, deliberately — rather than selling you hardware you don't need or moving data you can't afford to expose.
Keep it in-house
- Work over privileged, regulated, or classified records
- Anything where the data itself is the liability
- Tasks your governance rules forbid transmitting
- Systems where custody and audit must stay yours
Consider a managed service
- Tasks on public or non-sensitive data
- Bursty workloads cheaper to rent than to own
- Frontier capability not yet worth running locally
- Pilots, before committing to on-prem hardware
Find out what intelligence inside your walls is worth.
A needs review tells you where intelligent systems would pay off, what they'd cost to run on-premise, and what — if anything — belongs elsewhere.