On-Premise · GDPR

Your AI agent,
on your servers

RAG Weaver deploys on-premise in 2 to 4 hours via Docker. Your documents, conversations and data never leave your infrastructure. 100% GDPR compliant, no DevOps team required.

Why choose on-premise deployment?

In our recent projects, 50% started on SaaS and 50% chose on-premise, always for the same reason: data privacy policy.

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Data sovereignty

Your documents never leave your servers. Zero transmission to third parties, zero exposure to the US CLOUD Act.

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Native GDPR compliance

No complex transfer impact assessment. Your DPO validates in a day. Data stays in Europe.

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Private network integration

Accessible only from your VPN or internal network. Ideal for sensitive or regulated documents.

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Local LLM option

100% air-gapped with local Llama 3 or Mistral. No external API calls, no data transmitted.

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Full control

You manage updates, access and backups according to your internal IT policies.

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Predictable cost

A fixed subscription. LLM costs stay with your provider, without markup or per-message fees.

How does the on-premise architecture work?

RAG Weaver on-premise runs on 4 components deployed via Docker Compose on your server.

1

Vector database (Qdrant)

Stores vector representations of your documents. Lightweight (8 GB RAM for 100,000 docs), open-source, European-built.

2

RAG pipeline

Automatically chunks, indexes and updates your document sources. Connected to SharePoint, Confluence, PDFs, Word and more.

3

LLM (external or local)

Mistral/OpenAI API for performance, or local Llama 3 for 100% air-gapped. You choose based on your constraints.

4

RAG Weaver interface

No-code interface, channel management (widget, Teams, WhatsApp), analytics and business rules. Accessible from your internal network.

Minimum technical requirements

Server

8 CPU · 16 GB RAM · 200 GB SSD (for 50,000 documents)

OS

Ubuntu 22.04 LTS or RHEL 8+

Runtime

Docker 24+ and Docker Compose

Network

Outbound HTTPS access on port 443 (for LLM APIs)

Local LLM (optional)

NVIDIA RTX 4090 or A10 GPU, only for air-gapped mode

Deployment time

2 to 4 hours with RAG Weaver support

Frequently asked questions

What is an on-premise AI agent?

An on-premise conversational AI agent is hosted directly on your company's servers. Your documents, conversations and data never leave your infrastructure, unlike cloud SaaS solutions.

Is an on-premise AI agent GDPR compliant?

Yes, it is the most GDPR-compliant configuration. Data stays on your infrastructure, eliminating risks related to the US CLOUD Act. Your DPO retains full control over data processing.

Do we need a DevOps team to deploy RAG Weaver on-premise?

No. RAG Weaver on-premise deploys via Docker Compose in 2 to 4 hours. Our team supports the initial deployment and trains you on day-to-day management.

What are the minimum server requirements?

A dedicated server or VM with 8 CPU, 16 GB RAM, 200 GB SSD is sufficient to index 50,000 documents. Ubuntu 22.04 LTS or RHEL 8+, Docker 24+ and an outbound HTTPS connection.

Can we use a local LLM on-premise?

Yes. RAG Weaver supports local LLMs (Llama 3, Mistral 7B) via Ollama. This configuration is 100% air-gapped with no external calls. It requires a dedicated GPU (minimum NVIDIA RTX 4090).

Deploy your on-premise AI agent

30-minute demo + custom quote for your infrastructure.

Book a demo