Passo 1
Upload docs
Send PDFs, pages and internal knowledge base.
Journey: step 1 of 3
Trusted generative AI for Portuguese with private data.
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Coming soon (Q3 2026)
RAG & Vector DB
RAG combines LLMs with your own data for more accurate and auditable answers.
Documents become embeddings and are retrieved before final response generation.
This reduces hallucinations, improves context control and boosts PT-BR quality.
Mesmo sem equipe técnica, você consegue começar com um ambiente pronto e orientação passo a passo.
Passo 1
Send PDFs, pages and internal knowledge base.
Passo 2
Prepare semantic search index.
Passo 3
Vector retrieval + grounded generation.
POST /rag/query {"question":"What is the SLA?"}Exemplo do dia a dia
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Find answers without manual file scanning.
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Reliable answers grounded in company data.
| Metric | AutomaBotHub | OpenAI Assistants | Pinecone stack |
|---|---|---|---|
| Privacy | Dedicated environment | External SaaS | Architecture-dependent |
| PT-BR support | Specialized | Generic | Generic |
| Complexity | Low | Medium | High |
| Status | Q3 2026 | Available | Available |
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Upload → chunking → embeddings → index.
Question, retrieved context and final answer.
The architecture supports multiple providers based on use case.
Yes, isolation and access governance are core requirements.
Yes, PT-BR quality is a key goal.
Pricing details will be announced near launch.
Trusted generative AI for Portuguese with private data.
No complexity: pick a plan, we provision the environment, and you start with practical guidance.