AI Development × AI Transformation
AI Development Agencies for AI transformation Clients (September 2026)
AI Development agencies with verified AI transformation client evidence — ranked by depth of documented work, then editorial quality.
Each listed agency documents AI transformation engagements on its own site or in a published case study; the model is never inferred from a service list.
Ranked AI Development agencies for AI transformation clients
Rankings updated · Newest review
Berlin, Germany
Client evidence: 19 documented clients overall
Best for: German enterprises and federal or city administrations taking a machine-learning or LLM use case from feasibility to an operated system.
Babel
#2Madrid, Spain
Client evidence: 9 documented clients overall
Best for: Spanish and Portuguese banks, insurers and public administrations wanting AI delivered by a large integrator with the data work around it.
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.
Zühlke
#4Zurich, 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.
Vstorm
#5Wrocław, Poland
Client evidence: 6 documented clients overall
Best for: Mid-market operators putting an agent inside a product or a clinical workflow, where output has to be validated before it ships.
Dublin, 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: 5 documented clients overall
Best for: Governments and national-scale operators buying a system that has to run for years, not a model handed over at the end of a project.
Unit8
#8Lausanne, Switzerland
Client evidence: 5 documented clients overall
Best for: Industrial and financial enterprises building on Palantir Foundry, or weighing whether they should.
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.
N-iX
#10London, United Kingdom
Client evidence: 4 documented clients overall
Best for: Enterprises with large in-house engineering teams that want AI adoption or ML work measured against an agreed baseline.
Kruso
#11Copenhagen, Denmark
Client evidence: 4 documented clients overall
Best for: Consumer brands and public bodies adding AI search or an assistant to a commerce or content platform the same firm builds and operates.
Rewire
#12Amsterdam, Netherlands
Client evidence: 3 documented clients overall
Best for: Enterprises running an AI program who want their own team able to continue it afterwards.
DEPT
#13Amsterdam, Netherlands
Client evidence: 3 documented clients overall
Best for: Consumer brands taking an AI product to a large audience, from Inter's fan platform to Omoda's returns modeling.
Inspari
#14Copenhagen, Denmark
Client evidence: 3 documented clients overall
Best for: Nordic enterprises already running a Microsoft or Snowflake data platform that want AI built on top of it, not a standalone pilot.
Xomnia
#15Amsterdam, Netherlands
Client evidence: 3 documented clients overall
Best for: Dutch enterprises whose model problem turns out to be a data-platform problem.
DEUS
#16Amsterdam, Netherlands
Client evidence: 3 documented clients overall
Best for: Enterprises putting voice or conversational AI in front of their own customers.
Budapest, Hungary
Client evidence: 3 documented clients overall
Best for: Industrial and pharmaceutical groups that want their own engineers taught to run AI projects before they buy a system.
DAIN Studios
#18Berlin, Germany
Client evidence: 3 documented clients overall
Best for: Industrial and media organizations that want their own team running the system once it works.
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.
Amsterdam, Netherlands
Client evidence: 2 documented clients overall
Best for: Regulated institutions and retailers with a pricing, risk or monitoring problem that can be measured.
NextAI
Verified: the agency confirmed ownership from a company email address, and the listing passed editorial review#21Valencia, Spain
Client evidence: 2 documented clients overall
Best for: Spanish-speaking mid-sized companies replacing scattered CRM, ERP and spreadsheets with one operating layer.
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.
About this list
In a transformation program the development work that matters is the platform that makes the second use case cheaper than the first. Datatonic built Vodafone's AI Booster MLOps platform on Vertex AI over 18 months; it is live in more than eight markets, cut proof-of-concept-to-production to about four weeks, and its reusable templates were released as open source. Netcompany's DSB system is a swarm of per-line delay models orchestrated by its PULSE platform, and its Copenhagen Airport luggage model has run since 2016 with drift monitoring and retraining. Merantix Momentum's KRASS Optik recommender has served 900,000-plus customers daily on automated retraining since 2021. Zühlke's Julius Baer engagement is the platform layer for generative AI in a private bank rather than a single use case, and Inspari's Danske Fragtmænd toll model runs as Python inside the client's own Snowflake.
Sort on what the platform leaves behind and who can add to it. Ask each candidate for the time and cost of the most recent use case added to a platform it built, not the first, and whether the templates, pipelines and retraining jobs are yours. Datatonic's open-sourced templates and Inspari's model inside your warehouse sit at one end; Netcompany's PULSE, EASLEY AI and PERSEUS sit at the other, where the curator notes to confirm the terms of moving off them. The curator also notes that KRASS and Boehringer Ingelheim run as open-ended engagements, so ask what monitoring and retraining cost after go-live.
Intro by Gabor Kiss, curator · How we rank
Expert Insight
Why AI transformation fit matters for AI Development
A program is judged by what it institutionalizes: a use-case pipeline, a platform, trained people and a governance process that outlives the consultancy.
The EU AI Act turns governance from a slide into an obligation: inventories, risk classification and documentation are program deliverables, and the agencies here have published work that carries them.
Platform economics decide whether the second year is cheaper than the first: ask what the documented programs did to the cost of the next use case, not the first.
Frequently asked questions
22 agencies in our directory combine verified AI transformation client evidence with documented AI Development work. The current top-ranked are Merantix Momentum, Babel, Datatonic — ordered by depth of documented client evidence, then our editorial scoring (portfolio quality, credibility, completeness); placement is never paid.
Published rates across this page's agencies run €45–175 per hour (median ~€108). Project totals depend on scope — the rate index at /rates breaks the computed bands down by region, country and team size.
Every agency here documents AI transformation work on its own site or in a published case study, describing the engagement structure rather than a service-list claim. We never infer the model from portfolio tone, so this list only contains agencies that operate AI transformation engagements deliberately.
4 of the agencies on this page document an embedded / team-extension working model. See the team-extension page for the full verified list, or check the engagement chips on individual profiles.