For the last decade, building a startup was synonymous with getting an AWS account, but in 2026, that default is dead. Driven by the US CLOUD Act, aggressive GDPR enforcement, and the rising cost of hyperscalers, European CTOs are increasingly repatriating their infrastructure.
Building AI without US cloud giants is no longer a constraint, it is a competitive advantage. It guarantees data sovereignty, often lowers compute costs by 30-50%, and insulates your product from geopolitical regulatory shifts. This guide outlines the architecture for a fully European AI stack from the GPU metal to the inference layer.
The Compute Layer
The biggest myth in the industry is that only Azure and AWS have the best chips. In reality, European providers have built massive H100 and A100 clusters that are often easier to access and cheaper to run.
Scaleway (France)
Scaleway is the closest equivalent to a European AWS. They have invested heavily in their AI Supercomputer, Nabuchodonosor, to provide high-performance computing for model training. Their Managed Inference product lets you deploy open-source models (such as Llama 3 or Mistral) with a few clicks, mirroring the ease of AWS Bedrock but hosted entirely in Paris data centres. They are the default choice for startups that need a polished, developer-friendly ecosystem.
OVHcloud (France)
OVHcloud is the industrial heavyweight. As the largest cloud provider in Europe, they offer AI Endpoints and raw GPU instances at a scale that rivals the US giants. Their key advantage is vertical integration; they build their own servers and water-cooling systems, which keeps costs significantly lower than the market average. For data-intensive AI training runs where every cent of compute matters, OVH provides the most raw power per Euro.
Hetzner (Germany)
Hetzner is legendary among engineers for its price-to-performance ratio. While they are less focused on managed AI services, their dedicated GPU servers offer unbeatable value for teams that can manage their own bare-metal infrastructure. If you are building a custom inference engine and have a DevOps team that knows Kubernetes, moving from AWS EC2 to Hetzner can cut your infrastructure bill by 60% overnight.
The Model Layer
Relying on OpenAI’s API means sending your customer data to US servers. The European alternative is to host open-weight models yourself or use APIs from sovereign providers.
Mistral AI (France)
Mistral is the crown jewel of European AI. Their models (Mistral Large, Mixtral) consistently outperform their US equivalents on efficiency benchmarks. Crucially, they offer a “La Plateforme” API hosted in Europe, or you can download their weights and run them on your own Scaleway/OVH instances. Using Mistral ensures your intelligence layer is legally and culturally aligned with Europe.
Aleph Alpha (Germany)
For B2B and industrial applications, Aleph Alpha is the specialist choice. Their “Luminous” models are designed specifically for auditability and explainability, making them ideal for regulated industries like finance, law, and government. They enable full transparency into why a model gave an answer, a critical feature for compliance with the EU AI Act.
Silo AI (Finland/AMD)
Now part of AMD, Silo AI specialises in building custom, large-scale language models for enterprises. If you need a model trained from scratch on your proprietary data (e.g., a medical LLM for a hospital network) without that data ever leaving the EU, Silo provides the scientific workforce and infrastructure to build it.
The Vector Database
AI needs memory. While Pinecone is the US standard, the Netherlands offers a superior open-source alternative.
Weaviate (Netherlands)
Weaviate is an open-source vector database that you can self-host on any European cloud. It gives you complete control over your data indexes. Unlike US-managed services, where your vectors live in a black box, Weaviate lets you keep your customers’ “memory” on your own encrypted disks in Frankfurt or Amsterdam.
The Workflow
A fully sovereign architecture looks like this:
- Hosting: Rent dedicated GPU instances from Scaleway (Paris) or Nebul (Netherlands) for inference.
- Model: Deploy Mistral-Large via Docker containers on those instances.
- Memory: Run a Weaviate cluster on Hetzner dedicated servers for long-term data storage.
- Storage: Use OVHcloud Object Storage (S3 compatible) for raw datasets.
- Orchestration: Use Qovery (a French platform engineering tool) to manage deployments, effectively giving you the “Heroku experience” on your European cloud.
Conclusion
Building on a European stack is no longer about compromise; it is about resilience. By decoupling from US hyperscalers, you immunize your product against the US CLOUD Act (which allows US law enforcement to subpoena data hosted by US companies anywhere in the world). You also align yourself with the values of your European customers who increasingly view data privacy as a premium feature. In 2026, “Hosted in Europe” is not just a compliance checkbox; it is a sales strategy.
