Controlled AI for high-trust organisations.
Based in Geneva, Cytria works with organisations in Switzerland and internationally that want a Swiss-governed alternative to dependency on large foreign AI platforms.
The sector changes. The control principles do not.
Defined data perimeter
Every system operates on an explicit, approved data perimeter. No unauthorized data leaves your organisation.
Explicit human validation
High-impact decisions, advice, and communications remain subject to human review and sign-off.
Documented dependencies
All sources, models, and infrastructure components are clearly inventoried with documented records appropriate to agreed requirements.
Clear operational ownership
Operational roles and responsibilities are assigned to internal team members from day one.
Transferable systems
No vendor lock-in. Transfer, migration, and internalisation conditions are defined contractually for the selected deployment.
Training integrated into delivery
Capability building is embedded into diagnosis, deployment, and ongoing operation.
Five sector perspectives, one core promise
Select your sector to review recognisable workflows, human control boundaries and stage mappings.
SMEs
The Challenge
Limited internal IT resources and AI governance capacity, while employees already experiment with public tools.
The Outcome
Improve one workflow at a time with a defined data perimeter, explicit human validation and predictable scope.
Fiduciaries
The Challenge
Time pressure on accounting and compliance work, with client confidentiality, data-protection obligations and applicable professional-secrecy duties.
The Outcome
Deploy secure research and document handling assistants on sovereign Swiss infrastructure with strict controls.
Independent asset managers
The Challenge
Demanding regulatory obligations, high volume of market research and the imperative to maintain independent advice.
The Outcome
AI systems focused on research and document synthesis, preserving explicit human sign-off on decision briefs.
Municipalities
The Challenge
Administrative overload, scattered regulations and informal AI use risking exposure of citizen data.
The Outcome
Facilitate access to administrative regulations and dossier processing while preserving explicit public accountability.
Associations, foundations and NGOs
The Challenge
Small teams, heavy reporting obligations and sensitive beneficiary or donor information to protect.
The Outcome
Increase administrative capacity and retain institutional knowledge without oversized transformation programmes.
Different sectors, familiar situations
“Staff already use public AI tools informally.”
“Important knowledge depends on a few key people.”
“Repetitive administrative work consumes team capacity.”
“Sensitive information cannot be sent to unapproved third-party services.”
“A business process is known to be inefficient but lacks clear formalisation.”
“Management needs a clear, practical first step before committing budget.”
“An existing AI tool lacks operational controls and auditability.”
“New users require practical training and support directly tied to their workflows.”
Three stages: Diagnose, Deploy, Operate
Capability building begins during Diagnose, becomes system-specific during Deploy and continues through onboarding and operational reviews in Operate.
Diagnose
Clarify the situation, the workflow, the data perimeter, the risks, the readiness and the appropriate first step.
Explore Diagnose →Deploy
Test and deploy one controlled system at a time with clear human validation checkpoints and operator handover.
Explore Deploy →Operate
Operate, monitor, maintain and improve deployed systems with onboarding, refreshers and governance reviews.
Explore Operate →Inspectable evidence and documentation
Review our methodology, sample deliverables, architecture and engagement terms.
Bring the situation. You do not need to bring the solution.
Describe what is currently repeating, slowing your team down or requiring clearer governance. We will help identify the appropriate starting point.