PRIVATE AI, EU INFRASTRUCTURE, OPENAI-COMPATIBLE

Your LLM. Your servers. Your data.

Sovereign LLM inference for e-commerce merchants. Open-weight models, GPU servers in European datacenters, OpenAI-compatible endpoints. Your prompts, catalog and customer data never leave the tenant we operate for you.

Property Value Note
data.residency 100 % EU OVH, Scaleway, Hetzner, UpCloud
training.on.your.data 0 by default, zero retention
batch.throughput 10,000+ prompts per batch via Batcher.ai
api.compat OpenAI drop-in base_url switch

> 01 / ARCHITECTURE

Sovereign inference, end to end.

Three layers, one operator. Your GPU servers in EU datacenters, open-weight models we deploy and update, a secured API consumed by your applications. No third party in the middle, no token leakage to a US provider.

LAYER 01
GPU servers, EU.

Dedicated GPU instances, NVIDIA and AMD, provisioned at OVH, Scaleway, Hetzner or UpCloud. Hardened Debian, isolated tenant, monitored 24/7 by Fast-Mage sysadmins. No resources shared across clients.

LAYER 02
Open-weight models.

Llama, Qwen, DeepSeek, GLM, Kimi, gpt-oss, Codestral, plus Qwen-Embedding for RAG and FLUX for image, and other families on demand. We benchmark, quantize (GGUF, AWQ), and track new releases. Fine-tunes on your data stay on your tenant, full ownership and exit on request.

LAYER 03
Secured API.

OpenAI-compatible endpoints (chat, embeddings, vision), token-based auth, usage monitoring, rate limits. Open-WebUI included for your team's collaborative prompt work. Drop-in replacement for an existing OpenAI integration.

FLOW YOUR APP > FAST-MAGE API GATEWAY > PRIVATE VECTOR INDEX (RAG) > OPEN-WEIGHT LLM ON DEDICATED GPU > RESPONSE (EU only, zero retention by default)

> 02 / WHY SOVEREIGN

What changes vs. OpenAI or Anthropic.

Calling a US API from a French or European e-commerce stack means your catalog, customer messages, internal documents and prompts cross the Atlantic, fall under US jurisdiction (CLOUD Act), and contribute, by default, to training datasets you do not control.

Criterion Public US APIs Fast-Mage private AI
Data residency US datacenters, transit through US backbone EU datacenters, EU-operated
Legal jurisdiction US (CLOUD Act, FISA 702) EU, GDPR-aligned
Training on your inputs Opt-out, varies by plan and ToS update Zero, by default
Model ownership Closed weights, vendor lock-in Open weights, your fine-tunes
Pricing model Per token, unpredictable at scale Per GPU, predictable monthly
Trade-secret exposure Prompts and outputs leave your perimeter Stays within your tenant
API contract OpenAI / Anthropic native OpenAI-compatible, drop-in

> 03 / E-COMMERCE USE CASES

Built for merchants, not for demos.

Concrete workloads we deploy in production on Magento, WooCommerce, PrestaShop, Sylius and Akeneo stacks. Each pipeline is reviewed by a human engineer before going live.

USE CASE 01
Catalog generation, at scale.

Product descriptions, SEO metadata, translations across 5 to 20 locales, image alt text. Batcher.ai orchestrates 10,000+ prompts per run against your private inference cluster. Output is staged, diffed against the previous version, and pushed to your PIM or CMS on validation.

Stack: Akeneo, Magento, PrestaShop, WooCommerce
USE CASE 02
RAG on catalog and support.

Ingestion of product catalog, technical PDFs, internal wiki, past support tickets. Customer-facing assistants and internal copilots query a private vector index, with strict per-tenant isolation. Re-indexing is webhook-triggered on catalog updates.

Stack: any e-commerce CMS + custom embeddings
USE CASE 03
Review and message moderation.

Pre-filter incoming customer reviews, contact messages and Q&A submissions. Classification on toxicity, off-topic, spam and language. The model never sees content that would otherwise leave your perimeter to a third-party moderation service.

Stack: Magento UGC, custom forms, marketplaces
USE CASE 04
Internal copilots and agents.

Sales, support and merchandising teams query an Open-WebUI workspace connected to your private models, with shared prompt libraries. Multi-agent workflows (inventory checks, CRM enrichment, SEO drafts) via CrewAI or n8n integrate over the same OpenAI-compatible API.

Stack: Open-WebUI, CrewAI, n8n, custom scripts

> 04 / AI AGENT STUDIO

Agents that act on your business.

Beyond chat and batch, we deploy AI agents wired into your systems (catalog, CRM, helpdesk) that run recurring tasks under supervision. Built with your teams, hosted on your private infrastructure, never a black box.

AGENT 01
Pre-built agents.

Ready-to-use agent library for recurring e-commerce tasks: inventory sync and checks, CRM enrichment, SEO metadata generation and audit. Connected to Magento, Akeneo or your PIM over the API.

Scope: Inventory, CRM, SEO
AGENT 02
Multi-agent workflows.

Compose custom workflows where several agents coordinate: retrieve, reason, act, validate. CrewAI and LangChain-compatible orchestration, run on your private models.

Scope: Custom
AGENT 03
Real-time supervision.

Every agent is traced: triggered action, source, token cost, latency. Drift alerting, with a human validation loop on sensitive actions.

Scope: 24/7 monitoring
AGENT 04
On your private infra.

Agents run on your Fast-Mage AI hosting, on dedicated EU GPUs. Your catalog and customer data never leave our infrastructure.

Scope: 0 data outside the EU

> 05 / WHAT YOU GET

A turnkey private AI bundle.

01 Infrastructure

Inference cluster.

  • + Dedicated GPU servers (L40S, A100, H100)
  • + Load balancer across GPU instances
  • + Daily model updates, GGUF / AWQ conversions
  • + Hardened Debian, 24/7 monitoring
  • + OpenAI-compatible API gateway
02 Tooling

Batcher.ai included.

  • + Spreadsheet interface for bulk prompts
  • + 10,000+ prompts per asynchronous run
  • + Multi-provider routing (private + third-party)
  • + Recipe library, e-commerce templates
  • + Free core access for hosting clients
03 Workspaces

Team and agents.

  • + Open-WebUI for collaborative prompting
  • + Shared prompt libraries across teams
  • + CrewAI and n8n integration patterns
  • + Deep research API (private beta)
  • + Usage dashboards per team and per key
GDPR
EU-only data flow. Logs and indexes hosted within the European Union, on infrastructure operated by Fast-Mage.
TRADE SECRET
Catalog, prompts, fine-tunes and customer messages stay within your tenant. No silent training, no telemetry to third parties.
EXIT CLAUSE
Full export of weights, indexes and logs on request. No proprietary lock-in on the model layer.
CONTROL PLANE
Per-team API keys, rate limits, usage dashboards. Audit trail of prompts available on request, with configurable retention.

06 / FREQUENTLY ASKED

Frequently asked questions.

Five key points.

Answers reviewed by our engineers. If your question is missing, just write to us, quick reply, no sales script.

Q01

Where exactly does the inference run?

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On dedicated GPU servers hosted in European datacenters (OVH, Scaleway, Hetzner, UpCloud). Your prompts, embeddings and responses stay on infrastructure under our operational control. No traffic is routed to OpenAI, Anthropic or any US cloud provider unless you explicitly enable a hybrid route.

Q02

Is your stack compatible with my existing OpenAI integration?

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Yes. We expose OpenAI-compatible endpoints (chat completions, embeddings). Switching your SDK base_url and API key is usually the only change required. Existing tooling like LangChain, LlamaIndex, n8n, CrewAI or your in-house clients keeps working.

Q03

Which models do you deploy?

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Open-weight models selected with you. For chat and reasoning: Llama, Qwen, DeepSeek, GLM, Kimi, gpt-oss. For code: Qwen Coder, Codestral, Devstral. For vision: Qwen-VL, GLM vision, Llama multimodal. For RAG embeddings: Qwen-Embedding. For image diffusion: FLUX, Stable Diffusion. Other families on demand. We handle quantization (GGUF, AWQ), benchmarking on your GPU footprint, and continuous tracking of new releases. Closed proprietary models stay possible via a hybrid setup if a specific task requires it.

Q04

How does RAG on our catalog and support docs work?

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We ingest your product catalog, PIM exports, support tickets, internal wiki and PDFs. Content is chunked, embedded and stored in a private vector index that we operate. Queries combine retrieval with the LLM, with strict tenant isolation. Re-indexing is scheduled or webhook-triggered on each catalog update.

Q05

Who owns the data, the models and the fine-tunes?

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You do. Zero training on your data by default. Logs are kept only for the retention you choose, on the same EU infrastructure. Fine-tunes produced from your data are your property and stay on your tenant. We provide an exit clause: full export of weights, indexes and logs on request.

Q06

Do you offer Batcher.ai with the hosting?

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Yes. Batcher.ai is our spreadsheet-style interface to run 10,000+ prompts in parallel across multiple models with workflow orchestration. Core features are included free for our hosting clients. It connects to your private inference cluster or to third-party APIs you already use.

Question not answered?

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