Verified client fit
AI Agencies for Enterprises in Europe (September 2026)
Agencies with verified enterprise client evidence, ranked by portfolio quality and credibility.
Each listed agency evidences at least 2 documented enterprise clients. Combined, the agencies below document 152 client engagements.
Top picks
Documented clients include
NHS · Visa · Orange · Carrefour · Novo Nordisk · Bpifrance
Ranked agencies for enterprise clients
Rankings updated · Newest review
Top 30 of 87 agencies with documented enterprise work.
Adastra
#1Frankfurt, Germany
Client evidence: 10 documented clients overall
Best for: Banks, insurers and manufacturers that need AI put under approval paths, audit trails and cost limits before it scales.
Satalia
#2London, United Kingdom
Client evidence: 6 documented clients overall
Best for: Enterprises with a scheduling, routing or workforce-allocation problem big enough to justify operations-research specialists.
London, United Kingdom
Client evidence: 8 documented clients overall
Best for: Enterprises standardizing ML delivery on Google Cloud or AWS, especially where a regulator has to be satisfied.
Prague, Czech Republic
Client evidence: 5 documented clients overall
Best for: Large enterprises in finance, insurance, retail and e-commerce that need a production ML system built with a named internal data team.
Unit8
#5Lausanne, Switzerland
Client evidence: 5 documented clients overall
Best for: Industrial and financial enterprises building on Palantir Foundry, or weighing whether they should.
Artefact
#6Paris, France
Client evidence: 5 documented clients overall
Best for: Large consumer and industrial groups that want AI agents adopted across a workforce, not piloted in one team.
ML6
#7Ghent, Belgium
Client evidence: 5 documented clients overall
Best for: Enterprises and public bodies putting AI into production systems that already carry real traffic.
Faculty
#8London, United Kingdom
Client evidence: 3 documented clients overall
Best for: Enterprises and public bodies that need AI deployed under regulatory or safety scrutiny.
Visium
#9Zurich, 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.
Converteo
#10Paris, France
Client evidence: 4 documented clients overall
Best for: Retail and consumer brands putting a customer-facing agent into production, with the evaluation and rollback to match.
Helsinki, Finland
Client evidence: 5 documented clients overall
Best for: Regulated Finnish and Nordic enterprises that need an AI system governed, certified and operated, not just delivered.
Solita
#12Helsinki, 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.
Madrid, Spain
Client evidence: 4 documented clients overall
Best for: Enterprises already committed to Azure that want an AI system delivered by a team with Microsoft-stack depth and named references.
Rewire
#15Amsterdam, Netherlands
Client evidence: 3 documented clients overall
Best for: Enterprises running an AI program who want their own team able to continue it afterwards.
Ergo
#16Dublin, 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.
Berlin, Germany
Client evidence: 3 documented clients overall
Best for: Institutions buying the data platform underneath analytics, where uptime and migration risk matter more than model accuracy.
Ghent, Belgium
Client evidence: 5 documented clients overall
Best for: Enterprises adding AI to a product or support workflow they already run, with the delivery team embedded alongside their own.
Squirro
#19Zurich, 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
#20Zurich, 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.
Wavestone
#21Paris, France
Client evidence: 3 documented clients overall
Best for: Regulated organizations whose AI program has to satisfy a supervisor, an auditor or a board risk committee.
appliedAI
#22Munich, Germany
Client evidence: 2 documented clients overall
Best for: Industrial enterprises running an AI program that has to satisfy governance as well as engineering.
Civitta
#23Vilnius, 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
#24London, 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.
2021.AI
#25Copenhagen, Denmark
Client evidence: 4 documented clients overall
Best for: Enterprises and public institutions that want a named AI system built on a governance platform with a live production record.
DareData
#26Lisbon, Portugal
Client evidence: 10 documented clients overall
Best for: Enterprises automating a high-volume back-office or support workflow, with the NOS and Heineken deployments as the reference pattern.
Ghent, Belgium
Client evidence: 5 documented clients overall
Best for: Retail and manufacturing teams that want pricing, forecasting and assortment calls made by a model their analysts can run.
Dear Future
#28Copenhagen, Denmark
Client evidence: 4 documented clients overall
Best for: Consumer brands with first-party data already in the stack that want it turned into predictions the marketing team will actually use.
Limebit
#29Berlin, Germany
Client evidence: 2 documented clients overall
Best for: Pharmaceutical companies and statutory health insurers that need analysis to survive a regulatory review and the code to come with it.
Datasparq
#30London, United Kingdom
Client evidence: 6 documented clients overall
Best for: Operational businesses with data already flowing that want a system built on it rather than a strategy deck.
About this list
Enterprise AI buying differs from every other purchase on this register: the model is the easy part, and the surrounding apparatus—procurement, information-security review, model documentation, adoption beyond the pilot team—decides whether anything ships. Every agency on this page documents at least two engagements with organizations of roughly a thousand people or more, listed companies, or household names, and the published work reads accordingly.
Artefact's Bpifrance deployment put AI agents in front of 500 employees at a public investment bank. Converteo's voice agent for Orange publishes latency figures, adversarial testing and a production date. Faculty's work for the NHS AI Lab is validation infrastructure—the part that decides whether a clinical model is allowed to matter. Neurons Lab shipped Visa a twenty-language LLM content system in under two months, and Modulai's retrieval system for Novo Nordisk pulls clinical-trial evidence for a listed pharmaceutical group.
Read the roster with two questions. First, who actually staffs the engagement: at consultancies above a few hundred people, the named team matters more than the aggregate credentials. Second, what happened after the pilot. Enterprise AI work that stops at a proof of concept is the most common failure mode in this market, and the agencies ranked highest here are the ones whose case studies describe adoption, operations and handover rather than a demo. Scores rank portfolio quality and credibility; placement is never sold.
Intro by Gabor Kiss, curator · How we rank
Expert Insight
Why enterprise fit matters
Enterprise AI fails at the surroundings, not the model: procurement, security review, model documentation and adoption budgets decide outcomes, and an agency that has cleared them before will price and plan for them unprompted.
Reference checks work differently at this scale—an agency with two documented enterprise engagements can name a buyer who survived the same internal scrutiny yours will apply.
The pilot-to-production gap is widest here: ask for case studies that describe operations and handover, because a proof of concept that never shipped is the modal enterprise AI outcome.
Frequently asked questions
An organization of roughly 1,000 or more people, a listed company, or a household name at the time of the documented engagement—banks, insurers and public institutions classify by institutional status where headcount is the wrong frame. Every listed agency evidences at least two documented, named enterprise clients, counted across all documented clients our research read, with source URLs stored per client. Borderline cases classify downward, never up.
By reading, not by trusting. Each qualifying client comes from a published case study or engagement description our research actually opened, and the source URL is stored with the entry. Logo walls without published engagements carry no weight here—several agencies with impressive logos sit outside this list because nothing connects the logo to documented work.
Match the firm's scale to the program's. A global consultancy fits when the work spans many systems and business units and must clear formal governance; a specialist fits when the scope is a defined system and you want the senior people doing the work directly. The most expensive mismatch is a mid-sized build staffed by a large firm's junior bench at senior prices—ask who staffs the engagement before comparing rates.