// TECHNOLOGICAL SOVEREIGNTY
Your data is yours. Your infrastructure, too.
Traditional SaaS puts your data on servers you don't control, governed by rules you didn't negotiate and prices that can change at any time. We build AI systems where the decision about who sees what data goes back into your hands.
// SOVEREIGNTY ARCHITECTURE
The client's data lives at the center. AI queries come in and go out without real data crossing the perimeter. Privacy is structural, not optional.
// THE PROBLEM WITH TRADITIONAL SAAS
When your data lives on servers you don't control.
Every time you load company data into a cloud service, that data leaves your perimeter. It lives on infrastructure that isn't yours, governed by terms that can change, subject to the laws of the country where the server is, and accessible to the service provider. Three concrete consequences:
Regulatory risk
GDPR Art. 44-49 prohibits international transfers of EU data to countries without adequate protection. The €1.2 billion fine to Meta came from there. If you operate with European clients, their data on a US server is a legal problem.
Financial dependence
The SaaS price is decided by the provider. If they raise plans, you have no real alternative because your data is inside and migrating is costly. SaaS works as an indefinite rental.
Technology lock-in
The more you integrate a SaaS into your operation, the more expensive it is to leave. Providers design their APIs and formats so migration is costly. It's not a bug, it's the model.
// HOW WE DEPLOY
Three modalities. One sovereignty decision.
The systems we build can be deployed in three modalities. Each balances privacy, cost and speed differently. Most of our clients operate in hybrid mode — the sweet spot.
// SAAS
Managed SaaS
Cloud service, managed.
Virtual server dedicated to your company. We manage infrastructure, you access via browser. Deployment 3-5 days. Ideal for kick-offs or when sensitive data is low.
When to choose it:
When you're starting out and want speed without technical commitment. When the data involved doesn't require total sovereignty.
// ON-PREMISE
On-premise
Total sovereignty. Your server, your network.
The system is installed on your infrastructure. In air-gapped mode, zero internet connection. Data never leaves your company perimeter. Deployment 5-15 days. Maximum sovereignty, ideal for regulated sectors or highly sensitive data.
When to choose it:
When you operate in regulated sectors (health, finance, defense) or when compliance demands it.
★ RECOMMENDED
// HYBRID
Hybrid
The sweet spot. Privacy without on-premise cost.
Dedicated server under our control (or yours) with Data Shield active. Sensitive data never leaves the perimeter because Data Shield anonymizes it before it touches any external AI model. Keeps the cost advantage of SaaS and most of the sovereignty benefits of on-premise. Deployment 5-10 days.
When to choose it:
When you need real privacy but on-premise is too costly for your size. For most SMBs and mid-sized companies. What we recommend in 80% of cases.
// THE PROBLEM DATA SHIELD SOLVES
External AI engines never see your real data.
The most powerful AI engines today (GPT, Claude, Gemini) run on servers from OpenAI, Anthropic, Google. When a company uses them directly, the data it sends passes through those servers. For a company that values privacy, that's unacceptable.
Our answer is Data Shield: our own real-time anonymization layer that sits between your data and any external AI model. Where your system said "Juan Pérez, CUIT 20-12345678-9", the AI model sees "Person_1, Entity_1". The intelligence reasons over anonymous tokens; your system restores real data at the end, in your perimeter.
Result: you use the most powerful AI models on the market without them seeing a single real piece of data from your company or your clients.
See Data Shield technical detail →// PROTECTION LAYER
Five layers. Zero real data going out.
01
Detection
NER plus AR patterns (CUIT, CBU, DNI, addresses, phones). Local models, no data goes out.
02
Tokenization
Entities replaced by semantic tokens (Person_1, Entity_1, Amount_1). The type is preserved, the data is not.
03
Processing
The AI model only sees tokens. Reasons over anonymous structures.
04
Restoration
Tokens return to real data in your perimeter. Mapping lives in volatile memory, never persisted.
05
Audit
Full record with timestamp, exportable for regulatory compliance.
// REGULATORY COMPLIANCE
Compliance by architecture, not by goodwill.
How we design systems naturally complies with the main data privacy regulations. It's not an add-on, it's the architecture.
Europe
GDPR (Arts. 5, 6, 7, 15, 17, 20, 25, 28, 30, 32, 33, 35, 44-49), NIS2, DORA.
United States
HIPAA, GLBA, FCRA, FERPA, CCPA/CPRA, plus comprehensive laws in 20 states.
Latin America
LGPD (Brazil), Law 25.326 (Argentina), LPDP (Mexico).
Asia-Pacific
PIPL (China, with data localization), DPDP (India), PDPA (Singapore), Privacy Act (Australia).
Thirty minutes to understand your sovereignty model.
No commitment. We show you which of the three modalities fits your operation and your data best. If we see it makes sense, we propose it with concrete numbers.
Let's talk