Academic and University Research
Universities and research institutes want a frontier AI co-pilot that can read, synthesise and reason across restricted and export-controlled datasets without ever shipping that material to an unverifiable third-party location. Ethics boards and research-integrity offices increasingly bar dual-use, government-funded and commercially sensitive work from public cloud AI, because they cannot attest to where the data physically sits or who else can read it. Mickai installs the full stack on the institution's own GPU clusters, under keys the institution holds, so model inference and retrieval happen on campus and the data never leaves the building. The research IP, the funder's restricted material and the unpublished findings stay inside the estate, and no third party ever sees them.
Universities and research institutes, acting through the research office, the export-control and ethics functions and the central IT estate.
Export controls and ethics boards bar dual-use and funder-restricted research from unverifiable cloud locations, so the most valuable work is locked out of modern AI.
A sovereign co-pilot running on the institution's own GPU clusters, under its own keys, so synthesis over restricted datasets happens on campus.
The institution gets frontier-grade research synthesis while the IP, the restricted data and the dual-use risk stay inside the building and no third party ever sees them.
Five advantages hold across every sector, and they are architectural, not promotional. The third-party cloud-exposure vector is removed; your own physical, insider, and compliance controls remain yours.
The data never leaves your hardware, so no third party and no cloud-provider employee ever sees it. What happens in the server room stays in the server room.
You own the compute and the capability, so the system runs independent of the internet and of any cloud vendor's pricing, terms, or availability.
The data never crosses a geographical or digital border because it never leaves the building, which removes the cross-border-transfer and third-party-processing friction of UK GDPR, Schrems II, and the sector rules. You keep your own obligations.
Fine-tune and run retrieval on your deepest archives to build a hyper-customised co-pilot, with no risk of your proprietary edge training a public model or leaking.
After the hardware and licence, queries cost essentially electricity. A capital asset you own and depreciate, instead of volatile per-token cloud bills.
There is no third-party cloud path, so no competitor and no vendor insider can scrape, intercept, or subpoena your prompts or your fine-tuned weights from the internet. The trust vault is closed by architecture.
You own the software snapshot on your own hardware, so a change to a cloud vendor's terms, a model deprecation, or an outage cannot reach you. The system stays predictable and auditable on-premise as the rules evolve.
The specific rules that bar mainstream cloud AI from this sector's regulated data. Each one demands a named, auditable perimeter the operator controls, which a shared multi-tenant cloud cannot give.
The kind of organisation this serves, named illustratively from public information to characterise the market. These are target profiles, not customers: Mickai has no relationship, engagement, trial, or endorsement with any of them.
The enterprise studios that lead in this sector, drawn from the eighteen that sit on the one sovereign substrate. Each runs on hardware the organisation owns, under one set of operator-held keys, writing to one Open Audit Record.
Contract Review and Legal-Ops
Reads grant agreements, data-sharing and material-transfer agreements and export-control clauses, flags dual-use and restricted-use obligations before work begins, and keeps every contract on campus.
Executive BI
Gives pro-vice-chancellors and research offices a sovereign view of the grant portfolio, restricted-project exposure and cluster utilisation without exporting any of it to a cloud dashboard.
Training and LMS
Delivers researcher and student training on the co-pilot, on Trusted Research duties and on handling export-controlled material, with all course data held in the institution.
Compliance and Regulator Mode
Maps each project against ITAR, EAR, UK export controls and ethics-board conditions, and produces an evidence trail the institution can show to funders and regulators.
Sovereign Meeting Note-Taker
Captures ethics-committee, grant-review and consortium meetings on the institution's own hardware, so minutes covering sensitive research stay in the room.
See all eighteen on the sovereign services catalogue.
Research-intensive universities and national institutes sit on large volumes of restricted, funder-controlled and commercially valuable data that they are currently barred from putting through public cloud AI, leaving a fast-growing co-pilot capability gap precisely where the highest-value, most export-sensitive work happens. As funders and security agencies tighten Trusted Research and dual-use expectations, the institutions that can offer on-premises sovereign AI become the ones that can credibly win and run that restricted work.
Money won, money saved, risk removed, on hardware you own.
Restricted and export-controlled projects that could not previously touch cloud AI become workable on campus, protecting the grant income and the IP attached to them. The institution removes the cross-border-transfer and third-party-processing vector for its most sensitive datasets, while its own physical, personnel and ethics controls remain its responsibility. Per-seat and per-token cloud AI spend that the research office could never approve for restricted work is displaced onto GPU clusters the institution already owns, and synthesis that once stalled at the compliance gate now runs in-house.
Map the sovereign stack to your academic and university research estate.
Briefings are for organisations weighing a sovereign, on-premises deployment. Tell us about your estate and we will walk the pack, the regulatory crosswalk, and the deployment that fits your estate.