Private AI for business is artificial intelligence that runs on your infrastructure or in European data centres — never on a non-European provider's public cloud. Altovar builds it with open-weight models, EU inference, on-premise deployments and air-gapped options: the convenience of an AI assistant, without a single document leaving your perimeter.
Every prompt sent to a public cloud assistant is a data transfer to a non-EU jurisdiction. With contracts, case files and customer data in play, that is not an acceptable risk.
Revocable licences, shifting prices, models that disappear. An office that runs on public AI builds its processes on foundations it does not control.
European regulators expect data traceability, risk assessment and control over AI systems. Hard to demonstrate with tools whose processing happens elsewhere.
No lock-in to a single vendor: the catalogue starts from open-weight models (Qwen, Llama, Mistral and others) and extends to European models. Pick by language, cost and capability — and switch anytime without rewriting anything.
Inference runs on European infrastructure or on-premise, on your servers. For the most sensitive environments the air-gapped deployment works fully offline: no phone-home, no outbound calls.
The assistant answers from your archives — contracts, case files, ERP documents — with verifiable citations. Semantic search indexes your document perimeter, not the web.
From an entry profile on shared EU hardware up to dedicated GPUs and bare-metal servers in your data centre. Sizing follows real workloads, not a marketplace plan.
Offline AI for the office is not a stylistic exercise: it changes where data ends up, what operations cost, and what you can show an auditor.
The business documents the AI builds answers on, with inherited permissions.
Explore →Dedicated GPUs, dedicated servers and managed servers in EU data centres.
Explore →Assessment, integration and autonomous agents: the team that implements it.
Explore →We identify the use cases with the best impact-to-effort ratio — from contract Q&A to data extraction — and define model, placement and data perimeter.
Inference environment in the EU or on-premise, model selected from the catalogue, GPUs sized on real volumes. Operational in days, not months.
RAG indexing of your business documents, permissions aligned with who asks, citations on every answer. Tested with your vocabulary, not generic examples.
Monitoring, per-query costs under control, model upgrades when they pay off. If the regulatory picture changes, the infrastructure is already ready to prove it.
Yes — in the air-gapped configuration, inference and document search run fully offline, inside your network. Connectivity is only needed if you choose to integrate external sources.
No. In on-premise and air-gapped deployments processing happens on your systems; in hosted ones, inside EU data centres. No data is used to train third-party models.
It depends on model and load: shared EU profiles at entry level, scaling to dedicated GPUs or bare-metal servers. The initial assessment includes a cost estimate for your request volume.
Those tools process your data on the vendor's cloud. Here models, hardware and documents stay under your control: same user experience, a completely different data perimeter.
The architecture is built to answer both: EU data residency, access logs, processing traceability and documented risk assessment — the evidence an audit asks for.
We'll show how Altovar integrates into your infrastructure. No commitment, no sales pitch. Just a technical conversation.
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