The power of
private AI with
total sovereignty.

A private LLM is a language model run on your own or dedicated infrastructure, without sharing data with third parties. The MDA 2.1 LLM operates entirely in certified Brazilian data centers, ensuring national sovereignty and full compliance with the LGPD. Your corporate data never leaves Brazil — you maintain full control over access, use, and storage.

Public APIs charge per token consumed (variable pricing, in USD), send your data to external servers, do not guarantee LGPD compliance, and have unpredictable costs. The MDA 2.1 LLM charges a fixed price per user/month in BRL (R$ 103 Basic · R$ 107 Intermediate · R$ 110 Advanced starting at 100 users, with a linear discount down to BRL 89 (~USD 17) for 500+ employees). Data remains 100% private in a dedicated Brazilian data center, with LGPD compliance guaranteed by design.

The MDA 2.1 LLM uses a fixed price per user/month with a linear volume discount: R$ 103 (Basic) · R$ 107 (Intermediate) · R$ 110 (Advanced) for 100 employees, decreasing linearly to BRL 89 (~USD 17)/user for 500+. Examples: 100 Intermediate users = R$ 10.7k/month · 300 users = R$ 29k/month · 500 users = R$ 44.5k/month. Full implementation in 7 business days. Companies migrate from token-based APIs and save between 28% and 86% depending on the tier and volume, with an average ROI of 4.2 months.

Yes. It was developed with LGPD compliance in mind from the outset. It offers: role-based access control (RBAC), comprehensive audit logs of all interactions, data hosted in certified Brazilian data centers, the right to be forgotten implemented, and pre-configured DPIA (Data Protection Impact Assessment) reports.

Governance includes: granular access control by department and user, real-time monitoring of all queries, customizable acceptable use policies, immutable audit logs for compliance, automated alerts for suspicious usage, and executive dashboards with real-time usage, cost, and ROI metrics.

MDA LLM 2.1 isn't just a language model — it's an enterprise reasoning engine. While ChatGPT and Claude are generic models hosted on third-party servers in the US, MDA LLM 2.1 runs on a frontier MoE architecture (32B parameters · 3.3B active · 256k context · FP8) in a Private Cloud in Brazil. It's customized with your company's data (via RAG and fine-tuning), never shares your information, and includes safety guardrails to ensure it only does what your business allows.

Yes — and they don't just compete: in enterprise tasks, they already outperform them. Until 2023, open-source models were limited. But we've entered a new era with next-generation open-source Frontier Models, which have matched — and in many benchmarks surpassed — the reasoning capabilities of GPT-5.5 and Claude Opus 4.7, especially in programming, data analysis, and logical reasoning. The difference is that, because they are open-source, we can run them privately, securely, and at a much lower cost for you.

Quality doesn't drop — efficiency increases dramatically. The secret lies in the MoE (Mixture of Experts) architecture. To understand: imagine that OpenAI uses a "dense" model, where to answer the simplest question, the entire brain of 1 trillion parameters is activated (consuming vast amounts of tokens and processing power). MDA LLM 2.1 has 32 billion parameters, but activates only 3.3 billion per task. It's like having a team of experts and calling only the engineer for the engineering problem — not the whole room. The result: the same level of intelligence, burning a fraction of the tokens.

The business model of Big Tech companies (OpenAI, Google, Anthropic) is to profit from the volume of tokens processed in their cloud. To do this, they need massive models that can do everything (write poems, solve physics problems, translate Japanese). This "extreme generalization" consumes an absurd amount of computing power, and you're the one footing the bill in dollars. MDA breaks this cycle by focusing on business efficiency: we use cutting-edge open-source architectures, optimize compression (FP8 quantization), and run on our own infrastructure (vLLM). You stop paying for "wasted tokens" on generic tasks and start paying only for the actual infrastructure you consume. That's why we can charge R$ 107/user/month in Brazilian Reais, compared to Big Tech's bills of thousands of dollars.

Frontier Models are the most advanced and intelligent models available at the cutting edge of human knowledge in AI today. The open-source community releases Frontier Models at a much faster pace than proprietary companies. Since MDA is agnostic and runs on its own AI Gateway, as soon as a superior open-source model emerges on the market, we integrate it, test it, and make it available for your operation — without vendor lock-in. Your company will always run the smartest AI on the market, without rewriting a single line of code.

Tokens are the "currency" of AI. Every word read or generated consumes tokens. If your operation has 100 employees using AI to read long documents, analyze data, and generate reports, the volume of tokens skyrockets. Using a public model for this is like paying for a taxi when you could take a ride-sharing service: it's extremely expensive, and you don't control the route. The MDA LLM 2.1, with its more efficient architecture (MoE · 3.3B active) and running on a dedicated server (vLLM · FP8), does the same work while consuming far less processing power. Token savings = real savings at the end of the month and budget predictability.