Sovereign AI for EU Institutions
Twenty-four languages, twenty-seven member states, and a mandate to lead on the very rules it has to obey. The Union's institutions need AI that is European-native, multilingual by design, and governed to the standard the EU AI Act sets for everyone else.
Multilingual by design
Retrieval, agents and assistants work across the official languages on the institution's own documents, with citations to the source text.
The AI Act applied to itself
Model inventory, logging, human oversight and documentation built in, so the institution meets the obligations it asks of others.
European-native, no dependency
Built in Europe, run on European infrastructure, with open-weight models. Strategic autonomy as an operating condition.
An institution, body or agency of the Union works in every official language, across member-state administrations, on data that ranges from public to EU-classified. It has to apply the AI Act to itself, answer to the European Data Protection Supervisor and the Court of Auditors, and avoid strategic dependence on a non-European provider. The platform gives it multilingual AI on its own infrastructure, with the transparency and audit the Union asks of others.
Read this if you're leading digital transformation, IT, data, security or data protection at an EU institution, body, office or agency, or in a Commission directorate or an executive agency.
For the institutions, bodies and agencies of the European Union, Scrydon is the European-native sovereign AI and data platform that runs multilingual models, agents and analytics on the Union's own infrastructure, including EU-classified networks, with policy, identity and audit built to the standard of the EU AI Act and the supervision of the European Data Protection Supervisor.
It runs in the institution's own data centres, in a European sovereign cloud or fully disconnected for classified information, with open-weight models served locally and no dependency on a non-European provider in the loop.
Every language, every member state, and the rules you wrote
An institution, body or agency of the Union works in twenty-four official languages, across twenty-seven member-state administrations, on data that ranges from open to EU-classified. Legislation, consultations, correspondence and case files exist in every language, so translation is a workflow rather than a feature; a policy question needs data from national administrations that are separate controllers with their own legal bases; and classified and public information sit on networks that must never be connected.
The Union also holds itself to the standard it sets for everyone else. The AI Act applies to its institutions, the data-protection regulation for the institutions is supervised by the European Data Protection Supervisor, the Court of Auditors asks how public money was spent, and strategic dependence on a non-European provider for something as central as AI is a finding in itself. The AI that helps has to be multilingual by design, European-native, and governed in a way the institution can show.
Twenty-four languages — Legislation, consultations, correspondence and case files in every official language; translation is a workflow, not a feature.
Data across member states — Policy questions need data from national administrations that are separate controllers with their own legal bases.
Classified and public side by side — From open data to EU-classified information, on networks that must not be connected.
Held to the highest standard — The AI Act, the EU data-protection regulation for the institutions and the Court of Auditors all apply, and a non-European dependency is a strategic finding.
Multilingual, federated, governed
The platform grounds retrieval and agents in the institution's own documents, across the official languages, with citations to the source text, so an answer about a directive, a case or a consultation can be checked in the language it was written in. Agents prepare case files, translations, impact assessments and reports, and route anything discretionary to an official, who decides; the decision and the reasoning are recorded together.
Where a policy question needs member-state data, a data space lets each national administration publish governed data products under its own access policy, and the question runs as a query across them under a named legal basis, logged, with aggregation or pseudonymisation enforced where the law requires. Around all of it, AI governance keeps the model inventory, applies policy, logs every action and records human oversight, which is the evidence the AI Act, the Supervisor and the Court of Auditors ask for.
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Ground
Retrieval and agents answer from the institution's own documents, in the official languages, with citations to the source text.
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Federate
Data spaces let member-state administrations publish governed data products for a policy question under a named legal basis, without a central copy.
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Automate
Agents prepare case files, translations, impact assessments and reports; anything discretionary goes to an official.
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Govern and evidence
Model inventory, policy decisions, human oversight and an immutable audit log produce the AI Act and supervisory evidence.
Strategic autonomy, applied to the Union's own tools
Strategic autonomy is applied to the Union's own tools. The platform is European-native and runs in the institution's own data centres, in a European sovereign cloud or fully air-gapped for EU-classified information, with open-weight models served locally. There is no inference call, licence check or update path outside the perimeter, and an external model can be enabled only by explicit opt-in under policy, never by default.
Control follows the data and the actor. Classification markings are metadata enforced at retrieval, so nothing is served above the reader's clearance even inside the same network; agents act under scoped identities and every action is attributed; a cross-administration query carries its legal basis. The audit log, the policy decisions and the model inventory are the EU AI Act and ISO 27001 evidence, produced by running the platform, and the same governance model serves the open side and the classified side, so there is one stack to accredit.
European infrastructure — Runs in the institution's data centres or a European sovereign cloud, disconnected for classified information, with open-weight models served locally.
No non-European provider in the loop — No inference call, licence check or update path outside the perimeter. External models only by explicit opt-in.
Clearance at retrieval — Classification markings are metadata enforced when data is read, so nothing is served above the reader's clearance.
Evidence for the supervisor — Audit log, policy decisions and model inventory are the evidence for the AI Act, the Supervisor and the Court of Auditors.
Keep an eye on this space
What changed for your sector in European AI sovereignty, and what we learned in the field. A few times a year, no drip campaign.
Use cases for EU institutions
Multilingual services, cross-administration analytics and governed AI for the Union.
Citizen-Developer Case Automation
Digital Services
Challenge
Departments have a backlog of small, repetitive workflows — a permit reminder here, an intake form there — but IT teams cannot build a bespoke agent for every one.
Solution
A governed no-code builder lets policy and operations staff assemble their own AI agents from approved building blocks, with every workflow still subject to the same access controls and audit trail as an engineered agent.
Read more
Dozens of small workflows automated by the teams that own them, without adding to the central engineering backlog or bypassing governance.
Shadow AI Discovery for EU AI Act Readiness
Compliance & Risk
Challenge
Individual teams have quietly adopted their own AI tools and agents, so the organisation cannot produce a complete inventory ahead of EU AI Act high-risk obligations.
Solution
Continuous discovery surfaces every agent and AI tool in use across departments, classifying each against EU AI Act risk categories and routing unsanctioned use into governed alternatives.
Read more
A complete, defensible AI inventory and a measurable reduction in unauthorised tool use ahead of the 2 December 2027 enforcement deadline.
Multilingual Citizen Service Assistant for Municipal Counters
Citizen Services
Challenge
Municipal counters answer the same questions about permits, registration, waste and benefits in several languages, and the answers depend on local regulations that change every council term.
Solution
An assistant grounded in the municipality's own regulations, procedures and forms answers residents and counter staff in their language, cites the article it relied on, and hands over to a civil servant for anything that needs a decision.
Read more
Shorter queues, consistent answers across counters and channels, and a record of which regulation every answer was based on.
Cross-Ministry Data Space for Policy Analytics
Policy & Statistics
Challenge
Answering a policy question about, say, energy poverty needs data from tax, social security, housing and the energy regulator. Each ministry is the legal controller of its own data and cannot simply copy it into a shared warehouse.
Solution
A data space lets each ministry publish governed products from its own systems, under its own access policy, so analysts can join them for a specific, authorised question without any ministry giving up control of its data.
Read more
Policy questions answered in weeks instead of legislative cycles, with every access logged against the legal basis that allowed it.
What EU Institutions, Bodies & Agencies has to comply with
The regulations that decide whether AI can run on this data at all. Each page lists what the framework asks and which platform controls answer it — properties and refusals, not a checklist.
AI Act · EU AI Act
Applies to: Providers, deployers, importers and distributors placing AI systems on the EU market or whose AI output is used in the EU.
How the platform supports itGDPR · General Data Protection Regulation
Applies to: Any organisation that processes the personal data of people in the EU/EEA, whether established in the Union or offering goods, services or monitoring from outside it.
How the platform supports itISO 27001 · ISO/IEC 27001
Applies to: Any organisation that operates an information security management system — routinely required of software vendors, service providers and regulated enterprises by customers, regulators and procurement.
How the platform supports itISO 42001 · ISO/IEC 42001
Applies to: Any organisation that develops, provides or uses AI systems and wants a certifiable management system for doing so responsibly — providers and deployers preparing for the EU AI Act in particular.
How the platform supports it
What these outcomes actually run on
An institution's architect asks how multilingual retrieval is grounded, how AI use is governed to the Act's standard and whether it runs disconnected. These are the pages that answer those questions.
Sovereign Foundations
The zero-trust foundation the whole platform sits on — the same stack from air-gapped to cloud.
Enterprise RAG
Retrieval grounded in your ontology, so answers cite the record they came from.
AI Governance
Policy, data-loss prevention and audit applied to every AI action, with the evidence an assessor can read.
Data Spaces
Data shared across organisational boundaries without handing over ownership of it.
Air-Gapped
The full platform running offline, on networks with no route to the internet.
AI OS
The runtime that maps a process to steps, routes each step to a system, an agent or a person, and gives it the context to act.
Frequently asked questions
Does the platform work across all official languages of the Union?+
How does the platform help an institution apply the AI Act to itself?+
Can it run on EU-classified networks?+
How do we work with member-state data without a central copy?+
Is there any dependency on a non-European provider?+
Do you partner on tenders and framework contracts?+
Prefer to write? Email hello [at] scrydon.com and we will get back to you.
Keep going
Three routes from here: the rules you will be measured against, the platform these outcomes run on, and the sessions where we walk through them.
The rules that apply
Each regulation, what it asks, and the controls the platform provides for it.
The platform behind it
The AI Operating System, Analytics and Sovereign Foundations, page by page.
Every use case
All of them in one place, grouped by the sector that knows them best.
How – Inside the AI OS: running governed agents on your own cluster, live
17 Sept 2026, 09:00
Part 2 of the Sovereign AI series, for engineers and architects. No slides after minute five: an agent gets an identity and scoped permissions, calls tools over governed MCP, retrieves from the ontology rather than raw tables, runs inside the sandbox and is stopped when it steps outside policy, and everything lands in the audit trail — then the same stack brought up on a disconnected network. Properties and refusals, shown rather than claimed.
Other parts of Government
The other dedicated pages under Government, and the sector overview they hang off.
National & Federal Government
Ministries, agencies and national security bodies: air-gapped AI on classified networks, cross-ministry data spaces and EU AI Act governance across government.
Read the pageLocal & Municipal Government
Cities, municipalities and regions: multilingual citizen assistants, permit and benefit case work, and public-works analytics on the municipality's own rules and data.
Read the pagePolice & First Responders
Police, fire, dispatch and civil protection: case-file analysis, dispatch support and multi-agency incident pictures, inside the service and admissible.
Read the page
Partners
