The intelligence stays in the building.
Aspasia designs, installs, and maintains air-gapped AI systems for organizations whose data can't leave the premises. We don't disappear after install — we keep your systems current with the state of the art and own every upgrade along the way.
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 and kept current.
We stand up the full on-premise stack — compute, the AI foundation, and the specialists tuned to your work — and we keep it healthy and up to date. When a stronger method or model arrives, we handle the upgrade. You don't manage versions; you use the best available.
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.
Maximum value from your hardware. Minimum burden on your team.
We apply current state-of-the-art methods for running private AI on modest hardware — real capability without a data-center footprint. The specific techniques are our concern, not yours. What matters is that the system performs, stays secure, and improves over time without touching your data or your operations.
- PerformanceResponsive, capable AI on lean hardware — no data-center footprint required.
- SecurityEvery method we use is chosen to keep your data on your hardware. Nothing phones home.
- Our jobWe track the research, adapt the methods, and deliver improvements. You just use it.
Built to be trained, updated, and replaced — without touching your secrets or your uptime.
Trained on stand-ins, never your secrets
Each specialist is trained 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 system learns the shape of the task; your data never enters our training loop.
Updates without the downtime
Because the specialists learn from stand-ins, we can hold a faithful replica of your system on our own hardware. We fix, retune, or upgrade a specialist there, validate it, then swap it into your live system in place. Components change; the system keeps answering. Near-zero downtime, by design.
Always SOTA, never disruptive
The field moves fast. We track it continuously and upgrade both the foundation and the specialists as stronger methods arrive — it's a standing commitment, not an optional upgrade. The system you run next year won't be the one you bought this year, and you won't feel the transition 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 — always
We keep the foundation and specialists tuned, patched, and upgraded to the state of the art as the field moves. You get proactive outreach when a meaningful improvement is ready, not a support ticket queue. 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.