Verified client fit
AI Agencies for the Public Sector in Europe (September 2026)
Agencies with verified public-sector client evidence, ranked by portfolio quality and credibility.
Each listed agency evidences at least 2 documented public-sector clients. Combined, the agencies below document 150 client engagements.
Top picks
Documented clients include
Federal Environment Ministry (BMUKN) · University Hospital Leipzig · Freie Universität Berlin · RBB · Museum für Naturkunde · Groningen Seaports
Ranked agencies for public-sector clients
Rankings updated · Newest review
Unit8
#1Lausanne, Switzerland
Client evidence: 5 documented clients overall
Best for: Industrial and financial enterprises building on Palantir Foundry, or weighing whether they should.
Visium
#2Zurich, Switzerland
Client evidence: 5 documented clients overall
Best for: Pharma and life-sciences teams that need the method described in full when the client name cannot be.
Solita
#3Helsinki, Finland
Client evidence: 5 documented clients overall
Best for: Large organizations in regulated or industrial settings that need analytics and AI delivered with the data platform underneath it.
London, United Kingdom
Client evidence: 8 documented clients overall
Best for: Pharma, research and public-sector buyers with an NLP problem on unstructured documents that has to survive review.
Ergo
#5Dublin, Ireland
Client evidence: 4 documented clients overall
Best for: Irish public institutions and regulated financial firms adding AI to a Microsoft estate they already run.
Squirro
#6Zurich, Switzerland
Client evidence: 4 documented clients overall
Best for: Regulated enterprises buying a retrieval and knowledge platform with the delivery work attached, not a bespoke build.
Zühlke
#7Zurich, Switzerland
Client evidence: 8 documented clients overall
Best for: Regulated enterprises buying AI inside a system an engineering firm will also build, run and document.
Civitta
#8Vilnius, Lithuania
Client evidence: 3 documented clients overall
Best for: Public agencies and donor-funded programs that need an AI system designed, procured and delivered inside EU rules.
Kortical
#9London, United Kingdom
Client evidence: 8 documented clients overall
Best for: Enterprises with a defined prediction or document-automation problem that want a model in production in weeks.
Clockworks
#10Rotterdam, Netherlands
Client evidence: 4 documented clients overall
Best for: Utilities, regulators and logistics operators automating a manual visual inspection or counting task at network scale.
Version 1
#11Dublin, Ireland
Client evidence: 6 documented clients overall
Best for: Insurers, brokers and public bodies automating document-heavy back-office work with an ISO 42001-certified delivery partner.
Copenhagen, Denmark
Client evidence: 4 documented clients overall
Best for: Large public-sector and regulated organizations that want AI work grounded in named policy and delivery consultants.
Kainos
#13Belfast, United Kingdom
Client evidence: 5 documented clients overall
Best for: UK public bodies and regulated enterprises buying delivery at program scale, with AI as one workstream inside a larger build.
Adnovum
#14Zurich, Switzerland
Client evidence: 5 documented clients overall
Best for: Swiss institutions wanting a conversational AI system built into their own cloud and then operated for them.
Berlin, Germany
Client evidence: 3 documented clients overall
Best for: Research institutes and public bodies with a hard technical problem and a named specialist to answer for it.
App4You
#16Gdańsk, Poland
Client evidence: 5 documented clients overall
Best for: Polish public institutions and smaller operators that want a fixed-scope build with the price published before the first call.
Belfast, United Kingdom
Client evidence: 4 documented clients overall
Best for: Public bodies and research organizations that need messy data unified and throughput measured before any model work starts.
Berlin, Germany
Client evidence: 7 documented clients overall
Best for: Product owners adding AI to an app that already has users, rather than starting from a model.
DataNorth AI
#19Groningen, Netherlands
Client evidence: 12 documented clients overall
Best for: Northern Dutch organizations that need a build and the team trained to run it afterwards.
Babelscape
#20Rome, Italy
Client evidence: 3 documented clients overall
Best for: Publishers, IP offices and research institutions that need multilingual text analytics from a team that publishes its research.
Berlin, Germany
Client evidence: 3 documented clients overall
Best for: Public bodies and institutions that need an AI system they can operate, inspect and publish afterwards.
Rome, Italy
Client evidence: 6 documented clients overall
Best for: Public bodies that need an independent expert to specify, procure and supervise an AI program, not to build it.
Dublin, Ireland
Client evidence: 4 documented clients overall
Best for: Consumer-facing telecom and utility operators, and Irish public bodies, that need models tested and evidenced rather than built.
Nebuli
#24London, United Kingdom
Client evidence: 5 documented clients overall
Best for: Organizations wanting a private, self-hosted generative AI workspace over their own documents rather than a public LLM.
Codec
#25Dublin, Ireland
Client evidence: 2 documented clients overall
Best for: Irish public bodies and regulated organizations buying case management or a data platform from a long-established Microsoft partner.
Lausanne, Switzerland
Client evidence: 2 documented clients overall
Best for: Swiss institutions adding AI inside a larger systems program run by a long-established integrator.
Dublin, Ireland
Client evidence: 20 documented clients overall
Best for: Irish organizations already running Dynamics 365 or Power Platform that want Copilot and Azure AI advice from a Microsoft partner.
About this list
The roster here is small, and that is the honest consequence of the bar: at least two documented, named engagements with government bodies or public institutions each. Public-sector AI work is hard to publish—procurement rules, political sensitivity and long approval chains keep most of it invisible—so a documented public engagement carries more evidential weight than almost any commercial logo.
The documented work here is unusually concrete. Dr. Mark Wernsdorfer's AMPEL system runs clinical decision support across more than 1,500 beds at University Hospital Leipzig. Birds on Mars built irrigation forecasting for Berlin's street trees with the Federal Environment Ministry and CityLAB, and object digitalization for the Museum für Naturkunde. Hybrid Heroes delivered the rbb24 news app for the Berlin-Brandenburg public broadcaster and an e-mental-health platform with Freie Universität Berlin. DataNorth's programs run through Dutch public institutions, from the association of municipal social-services directors to Groningen Seaports.
Public buyers should read this list differently from the commercial pages. Ask how the agency handled the tender and what documentation it produced for the record, because an agency that has survived public procurement once is materially cheaper to work with the second time. And ask early about the EU AI Act: public-sector deployments sit disproportionately in its high-risk categories, and the difference between a partner who has already documented a system for review and one who has not shows up at exactly the wrong moment.
Intro by Gabor Kiss, curator · How we rank
Expert Insight
Why public-sector fit matters
Public procurement is a skill separate from engineering—an agency that has already won and delivered under tender rules costs less in process friction than one learning them on your project.
Public deployments carry documentation and transparency obligations commercial work does not, and the agencies here have published work that survived them.
The EU AI Act lands hardest on public-sector use cases—partners with documented public systems are further along the compliance curve than the market average.
Frequently asked questions
Government bodies and public institutions only: ministries, municipalities, public universities and hospitals, public broadcasters. State-owned commercial operators classify as B2B or consumer by their engagement, not here. Every listed agency evidences at least two documented, named public-sector clients, with source URLs stored per client, and borderline cases classify away from this page rather than onto it.
Because the evidence bar does not bend for a thin market. Public-sector AI work is systematically underpublished—procurement rules and political sensitivity keep most engagements out of case studies—so many agencies that genuinely serve public clients cannot document it. We list what is verifiable rather than padding the page, and the roster grows as agencies publish.
Materially. Public-sector deployments sit disproportionately in the Act's high-risk categories—essential services, law enforcement adjacency, decisions affecting citizens' access—which brings documentation, human-oversight and transparency duties into scope. Ask candidates what they have already documented for a conformity or model review; an agency answering with artifacts rather than architecture diagrams has done the work before.