Government and Public Sector

Sovereign by design, explainable by obligation

In-country and air-gapped AI for ministries and municipalities: citizen services, case triage, and a decision trail a public body can defend.

  • In-country and air-gapped
  • National language models
  • Procurement-ready evidence

Sovereignty

The data does not leave, and you can prove it

Residency is an architectural property, not a contractual promise: open-weight models inside your jurisdiction, offline mirrors so a disconnected estate can still be patched, and logs showing where every inference ran.

  • Open-weight models hosted inside your jurisdiction
  • Air-gapped clusters with a documented patch route
  • Bills of materials with chain-of-custody records

Citizen services

Not every citizen has an app

One assistant across web, WhatsApp, SMS, the telephone line and the counter. Voice is what reaches older and rural citizens, so it is built first rather than retrofitted.

  • web
  • WhatsApp
  • SMS
  • voice / IVR

Accessibility

WCAG 2.2 AA

tested on every public-facing interface we deliver, including voice and chat

Casework

Triage, not automated decisions

The recoverable time is in getting the right case to the right desk with the right documents attached. Determinations affecting rights stay with a named officer.

Records

Public records and information access

Classification-aware retrieval with page-level citations, and candidate redaction of personal and exempt material for a reviewing officer to confirm.

  • FOI
  • retention
  • redaction
  • audit log

Defensibility

Reasons a committee can read

Every output carries its sources, the rule it relied on and the officer who approved it, in an immutable log that outlives a change of supplier.

  • EU AI Act
  • ISO 42001
  • NIST AI RMF
  1. Intake Web, WhatsApp, SMS, voice or the counter
  2. Classify and check Completeness, urgency, vulnerability flags
  3. Route with evidence Confidence score and the documents attached
  4. Officer decides The signature stays with a named person
  5. Audit trail Sources, rule applied, override, immutable
A citizen request moves through the service, and every step leaves evidence an ombudsman can follow.

Deployment

  • Government cloud
  • National data centres
  • On-premise
  • Air-gapped
  • Offline registries

Models

  • Open-weight models
  • National language fine-tunes
  • Azure OpenAI
  • Locally hosted inference

Regulation

  • EU AI Act
  • GDPR
  • KVKK
  • UAE PDPL
  • National FOI law
  • Retention schedules

Standards

  • ISO/IEC 42001
  • ISO/IEC 27001
  • NIST AI RMF
  • WCAG 2.2 AA

Channels

  • Web portal
  • WhatsApp
  • SMS
  • Voice / IVR
  • Counter systems

Three ways in. Stop after any of them.

3–5 weeks

Feasibility and sovereignty assessment

Which services are automatable, what residency permits, and an indicative architecture you can put straight into a tender.

Feasibility assessment, deployment architecture, procurement-ready requirements

10–16 weeks

Pilot service

One service line built end to end inside the target deployment model, against a measured baseline.

Working service, national-language evaluation set, officer review interface

Ongoing

Programme delivery and operation

Rollout across service lines, operation under an SLA inside your environment, and transfer to your own team.

SLA operation, periodic red-teaming, maintained evidence pack, knowledge transfer

Questions

Yes, and it is most of what we do. In-country deployment runs open-weight models on government cloud, a national data centre or your own hardware; disconnected sites get offline artefacts and a patch route. We have delivered into the Türkiye Ministry of Health, Turkmenistan eHealth and the Saudi Arabian government.

Every output carries its sources and the rule it relied on, every override is recorded, and the log is immutable and exportable. Determinations affecting rights stay with a named officer. If a use case cannot be made explainable to that standard, we say so before the procurement rather than after the pilot.

When the service is broken rather than slow. If eligibility rules contradict each other, or three departments disagree about who owns an outcome, AI will industrialise the confusion in a plausible tone of voice. Fix the rules and the ownership first. If the policy is a decision table, use a decision table.

Bring us the constraint, not the brief

Regulator, budget, deadline, legacy core, a board that has been burned once already. Tell us what you are working around.