Technical Sovereignty in the AI Era
From Vibe Coding to Elite Engineering. Model Shielding, Local Inference, and Prompt Governance for companies that don't accept black boxes.
The New Attack Surface
Artificial Intelligence without engineering is a vulnerability.
PII Leakage in Prompts
Sensitive data sent to public APIs without sanitization or control.
Agent Hallucination
Inaccurate or dangerous responses generated by models without structured RAG.
Shadow AI & Dependency
Uncontrolled use of AI tools (SaaS Risk) and critical dependency on third-party APIs.
Tech86 AI Engineering
The Sovereignty Stack
Local Inference Clusters
Deploy Llama 3, Mixtral, or Qwen on own infrastructure (avoiding data exfiltration).
Secure RAG Pipelines
Information retrieval architecture where company data never trains public models.
AI Red Teaming
Offensive testing against your agents (Prompt Injection, Jailbreak).
Environment Hardening
Use of Rootless Docker, network isolation (Tailscale/Ziti), and input/output sanitization.
Journey to Sovereign AI
From diagnosis to secure implementation in 4 steps.
Diagnosis & Security
Mapping sensitive data, infrastructure audit, and defining success KPIs.
Tailored Architecture
Infrastructure design (On-prem or Edge), GPU sizing, and foundational model selection (Llama, Mistral).
Engineering & RAG
Proprietary data ingestion, vectorization pipelines, and building the corporate "brain".
Deploy & Hardening
Deployment in isolated environment (Air-gapped), Red Team tests (simulated attacks), and team training.
Artificial Intelligence Stack
We work with state-of-the-art open models and inference infrastructure.
Corporate AI FAQ
Common questions about Private AI implementation.
Privacy and Cost. With local LLMs (Llama 3, Mistral), your data never leaves your infrastructure, ensuring full LGPD compliance and industrial secrecy. Plus, it eliminates token costs of public APIs.
It's a technique that connects the AI's "brain" to your documents (PDFs, Databases). The AI queries your knowledge base before answering, ensuring accurate responses based only on your data, reducing hallucinations.
It depends on the model. For optimized model inference (Quantized), a consumer GPU (RTX 4090) may be sufficient. For training or massive models, we size clusters with A100/H100 GPUs.
We use RAG with source citation (the AI shows where it got the information) and "Grounding" techniques. If the information isn't in your database, the AI is trained to answer "I don't know" instead of inventing.
Lead the AI Revolution
Talk to our AI and Security engineers.
Quick chat.
Address
Avenida Paulista, 1636 - São Paulo - SP - 01310-200