Data sovereignty
Documents, conversations, customer data and prices travelling to servers outside your control.
Sovereign AI · Alliance with a private data centre in Spain
AI with your data. Without your data ever leaving home.
Artificial intelligence and machine learning applied to your business, running on your servers or in a private data centre in Spain. Zero exfiltration. Fully auditable.
- 0 datacrossing the EU border
- Flat costno pay-per-token, no surprise price changes
- Dedicated GPUsto train and serve your own models
- ENS · GDPR · EU AI Actcompliance by design
01The context
You wanted AI. You ran into a data problem.
80% of companies are already testing large language models (LLMs). Almost all of them do it by sending their data to an external provider outside the European Union. That shortcut comes at a price.
Vendor dependency
Price rises of up to 200%, changing terms of use and models that disappear without notice.
Regulatory compliance
The EU AI Act, GDPR and sector rules, more demanding every year.
Results you can’t act on
Generic chatbots that don’t know your business and off-the-shelf predictions that ignore your operations.
The problem isn’t AI. It’s how and where it runs. With open models and the right infrastructure, AI can run inside your perimeter with the same capabilities and without exposing your data.
02The proposal
Two specialists, one complete solution.
Datalsia brings hands-on experience delivering data and AI projects in industry, energy, retail, agriculture and services. Our partner, a private data-centre operator in Spain with its own infrastructure and certifications, brings full data sovereignty. Together we cover the whole stack.
Pillar 1
Data, machine learning and applied AI
- End-to-end design and delivery of AI and ML projects.
- Dashboards and forecasting: sales, revenue, inventory and churn.
- Machine vision and industrial predictive maintenance.
- Governed AI assistants over documentation and Text-to-SQL.
- Explainable, auditable models (XAI).
Pillar 2
Private data centre in Spain
- Own infrastructure, no foreign hyperscalers.
- Dedicated GPUs for LLM training and inference.
- Per-client isolation, private networks and local backups.
- 24/7 operations, service level agreement (SLA) and support in Spanish.
- ENS, GDPR and EU AI Act compliance by design.
One model. One project. One infrastructure. One invoice.
03What we build
AI assistants that know your business.
Trained or fine-tuned on your information, connected to your systems and with full traceability of every answer.
Assistants over your documents
Answers with cited sources over manuals, contracts, regulations or case files (RAG), without making things up.
Natural-language queries
Ask your ERP or database without writing SQL. Governed Text-to-SQL with permissions and audited access.
Voice-driven dashboards
With Dagenia, ask out loud for the chart you need: metrics, filters, thresholds and comparisons on the spot, in six languages.
Plant assistant
Summarises active alarms, sensor readings and shift handovers, prepares the plant report and notifies the right people.
Agents that act
They write work orders, send messages, prepare campaigns and trigger operational actions, always with human approval.
Service avatars
Voice service for customers or citizens, multilingual and trained on your information.
04Where it applies
Six sectors. Twenty-four real use cases.
These are the projects that most often make sense to run in a private environment.
Agriculture & cooperatives
- AI assistant per crop and season
- Harvest and demand forecasting
- Water stress from satellite and sensors
- Auction price prediction
Retail & distribution
- Sales and promotion forecasting
- B2B and consumer churn
- Inventory and replenishment optimisation
- In-store demographic analytics
Industry & manufacturing
- Predictive maintenance of machinery
- Machine vision for quality control
- Production and OEE forecasting
- Work-order analytics
Banking & financial services
- ATM and cash usage forecasting
- Transaction fraud detection
- Regulatory assistant
- Explainable risk scoring (XAI)
Hospitality & tourism
- Occupancy and revenue forecasting
- Staff absenteeism prediction
- Private AI assistant for guests
- Review and satisfaction analysis
Health & public sector
- Assistant over private clinical records
- Care demand prediction
- Explainable diagnostic models
- Document processing with RAG
05Why private
When data is sensitive, the environment matters.
Some of our projects, seen from the infrastructure decision.
Predictive maintenance
Vibration, temperature and operating hours are sensitive plant data. Here a private environment is almost mandatory.
−32% unplanned downtime in the pilot
Revenue forecasting
Intensive what-if simulations with LLMs call for local GPU power and clean ERP or CRM data.
Average error of 4%
Inventory optimisation
An external provider would see your margins and purchase volumes. Better on your own infrastructure.
€120-200k freed per €1M of stock
Customer churn
Sending customer data to a cloud LLM is a risk zone. The private assistant prepares campaigns without exposing it.
Up to 37% of customers won back
06Infrastructure decision
Private data centre vs public cloud.
Eight dimensions that matter when deciding where AI runs. Both models make sense, and many projects end up hybrid, but with sensitive data the balance tips clearly.
Where does your data travel?
Data outside the EU
0 B
Cost
Flat and predictable
Compliance
ENS · GDPR · EU AI Act by design
| Dimension | Private data centre (Spain) | Public cloud (outside the EU) |
|---|---|---|
| Data sovereignty | Data never leaves your servers | Data travels outside the EU |
| Regulatory compliance | ENS, GDPR and EU AI Act by design | Contractual annexes and jurisdictional grey areas |
| 24-month cost | Predictable investment, flat cost | Pay-per-token: scales with usage, unpredictable |
| LLM fine-tuning | No limits: your own model, no leaks | Limited by the provider; prompts visible to third parties |
| Latency and availability | Private network and local contractual SLA | Depends on the provider and public connectivity |
| Vendor lock-in | Low: open, portable models | High: proprietary APIs and unannounced changes |
| Set-up | Somewhat slower (weeks): needs design | Almost instant, very easy to start |
| Talent required | Infrastructure operations and ML (we provide them) | ML only: infrastructure is abstracted away |
For machine learning on sensitive data, and especially for corporate LLMs, a private data centre stops being an option and becomes the default choice.
Contact
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Tell us about your challenge by email or phone. In a first, no-strings session we align scope and approach, and tell you honestly whether we can help.
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