Insurance and Actuarial
Insurers and actuarial teams need to price risk on the most sensitive material a person owns: medical histories, criminal records, financial exposures and corporate liabilities. That same material is exactly what cannot sit on a third-party cloud, because special-category processing, high-risk AI obligations and prudential expectations all converge on it at once. Mickai runs underwriting models, claims adjudication and fraud screening locally, on hardware the insurer owns under keys it holds, so no client risk profile is ever handed to an external processor. The data never leaves the building, and the model still produces accurate, custom premiums with a fairness and explainability trail behind every decision.
Insurers, reinsurers, MGAs and actuarial teams that price and adjudicate risk on highly sensitive personal and corporate data.
Medical underwriting, criminal checks and liability exposures feed pricing yet cannot lawfully or safely sit on a third-party cloud under Article 9 and high-risk AI rules.
Underwriting, claims adjudication and fraud screening run offline on hardware the insurer owns, under its own keys, with no client risk profile leaving the building.
Accurate, custom premiums and faster claims with a built-in fairness and explainability trail, and no risk profile ever seen by an external processor.
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.
Underwriting and Actuarial
Underwriting and actuarial models run offline on the insurer's own hardware, so medical and financial inputs to premium pricing never reach a third-party processor. Claims adjudication is reasoned through on the same sovereign substrate, so loss data and reserving judgements stay under the insurer's keys.
Fraud and Anomaly Detection
Fraud and anomaly detection screens claims and applications locally, keeping suspect-case data and investigative signals inside the building.
Compliance and Regulator Mode
Compliance and Regulator Mode produces the fairness, explainability and decision-audit trail that high-risk insurance AI and FCA conduct rules call for.
Audit
Audit captures an immutable record of every pricing and claims decision, so reserving judgements and model outputs can be evidenced to regulators and internal auditors without exporting the underlying data.
Executive BI
Executive BI reports portfolio risk, loss ratios and pricing performance to the board without exporting the underlying policy and claims data.
See all eighteen on the sovereign services catalogue.
Insurers are under simultaneous pressure to personalise pricing with richer data and to prove that the same data and models are fair, explainable and properly governed, a combination that makes cloud AI a growing legal and reputational liability rather than a shortcut. A sovereign substrate lets carriers, reinsurers, MGAs and actuarial consultancies adopt advanced underwriting and claims AI while keeping the most regulated material entirely in-house.
Money won, money saved, risk removed, on hardware you own.
Insurers win sharper, more individualised premiums and faster claims adjudication while removing the third-party cloud-exposure vector for medical, criminal and liability data; physical and insider controls remain the insurer's own. The fairness and explainability trail is generated as the work is done, shortening regulatory and internal-audit cycles, and the recurring per-seat and per-call cost of external AI services is displaced by capacity the insurer owns outright.
Map the sovereign stack to your insurance and actuarial 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.