Galene.AI Deploys a Sovereign-by-Design Conversational AI Platform on Scaleway
Galene.AI built a fully sovereign, self-hosted conversational AI platform running on Scaleway's GPU infrastructure, engineered so client data, models, and compliance remain entirely within European jurisdiction. The platform deploys as a private Kubernetes cluster, either on-premise or within a private Scaleway cloud, with all AI inference processed locally on Scaleway GPUs (from 2xL40S to H100-based configurations) rather than through external API calls. Data is encrypted in transit (TLS 1.3) and at rest (AES-256). The platform includes an agentic framework using Model Context Protocol (MCP) to connect private AI agents to internal knowledge bases and enterprise systems (CRMs, ERPs), and a built-in governance layer called Generative Shield that enforces real-time compliance across cybersecurity, ethical/legal, data protection, and output-accuracy dimensions. Scaleway's data centers are located exclusively in the EU (France, Poland, Netherlands), which the companies say eases GDPR data-residency compliance and EU AI Act compliance. Galene.AI's REST API is compatible with OpenAI's API specification.
Overview
Galene.AI built a fully sovereign, self-hosted conversational AI platform running on Scaleway's GPU infrastructure, engineered so client data, models, and compliance remain entirely within European jurisdiction. The platform deploys as a private Kubernetes cluster, either on-premise or within a private Scaleway cloud, with all AI inference processed locally on Scaleway GPUs (from 2xL40S to H100-based configurations) rather than through external API calls. Data is encrypted in transit (TLS 1.3) and at rest (AES-256). The platform includes an agentic framework using Model Context Protocol (MCP) to connect private AI agents to internal knowledge bases and enterprise systems (CRMs, ERPs), and a built-in governance layer called Generative Shield that enforces real-time compliance across cybersecurity, ethical/legal, data protection, and output-accuracy dimensions. Scaleway's data centers are located exclusively in the EU (France, Poland, Netherlands), which the companies say eases GDPR data-residency compliance and EU AI Act compliance. Galene.AI's REST API is compatible with OpenAI's API specification.
This entry has 12 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
For many European organizations, adopting powerful large language models through public SaaS platforms means sending data to third-party ecosystems, often outside the EU, creating compliance risks with GDPR and the upcoming AI Act, along with issues of data sovereignty, intellectual property control, and vendor lock-in.
The solution
Galene.AI built a sovereign-by-design conversational AI platform that deploys on the customer's own infrastructure, on-premise or in a private Scaleway cloud, running as a private Kubernetes cluster. All AI tasks are processed locally on Scaleway GPUs (from 2xL40S to H100 based configurations), eliminating external API calls to third-party models, and data is encrypted in transit (TLS 1.3) and at rest (AES-256). Its agentic framework uses the Model Context Protocol (MCP) so private AI agents can securely access internal knowledge bases and connect to enterprise systems like CRMs and ERPs, and a built-in governance layer called Generative Shield enforces real-time compliance across cybersecurity, ethical/legal, data protection, and output-accuracy dimensions. Galene.AI's REST API is fully compatible with OpenAI's API specification.
Reported business value
The sovereign-by-design architecture is intended to give companies full control over their data, models, and compliance posture, and Scaleway's GPU-based licensing model is designed to eliminate expensive per-seat SaaS costs and vendor lock-in.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other technology & software entries in the register.
HP crafts marketing campaigns that resonate with customers using Databricks and Uniphore
HP centralized first-party customer data on the Databricks Data + AI Platform with Delta Lake and Unity Catalog, and connected it to Uniphore's HybridCompute for federated query pushdown, cutting campaign setup from 2 weeks to 2 hours and processing 400 million records in seconds.
Transforming Weather Forecasting with Lakeflow Jobs
AccuWeather migrated from on-premises infrastructure to Databricks and Lakeflow Jobs, working with Datadog for observability, to unify diverse weather data formats and orchestrate 4,500+ weekly jobs. Lakeflow Jobs coordinates the ingestion of multiple weather models, triggers machine learning processes that weight and blend different forecasts, and manages complex job dependencies for reinforcement training workflows used in AccuWeather's proprietary forecasting engine. AccuWeather reports 3x faster dataset development (three months to one month per dataset), a 50% reduction in unactionable alerts, and 50% cost savings on serverless job usage.
AccuWeatherLakeflow Jobs · Delta Sharing · DatadogAdobe brings creativity to life with Databricks
Adobe uses the Databricks Data + AI Platform for end-to-end data management that unifies all data and AI at scale, with 20% faster performance. Databricks equips over 92 teams at Adobe to unify data from financials, sales, products, customers and employees so they can drive personalized experiences across Adobe's digital platforms with AI.
Supermetrics: Helping Marketers Redefine Efficiency with AI-Powered Data Analysis
Supermetrics, a Finland-based marketing intelligence platform serving 15,000+ customers across 132 countries, built an AI agent on Google Cloud using Vertex AI Agent Builder and the Agent Development Kit (ADK) that autonomously manages data connections, fixes pipeline errors, and analyzes campaign performance in real time, suggesting new creative options using Imagen. The agent automates the weekly marketing reporting cycle that previously took performance marketers up to four hours, reclaiming over 15 hours per month per marketer for strategy and creative testing. The system uses a central AI agent that interprets natural language requests and delegates tasks to sub-agents, and stores 'core memories' of user preferences for personalized context.
Supermetrics· FinlandGoogle Cloud · Vertex AI Agent Builder · Agent Development Kit (ADK) +1
Was this helpful?
Your feedback helps us improve our use case database