Private ChatGPT
Your team already uses AI. Give them a private one.
Somewhere in your company, right now, someone is pasting client data into a public chatbot — because it helps them work. Banning it doesn’t stop it; it just hides it. The fix isn’t a policy. It’s a better, private alternative they’ll actually prefer.
The shadow-AI trade: every public prompt trades a little confidentiality for a little productivity. A private ChatGPT keeps the productivity and ends the trade — same experience, your infrastructure, your rules.
A ChatGPT-class workspace
A chat interface your team already knows how to use — running on open-weight models served from private EU GPUs, behind one company login.
Your knowledge, privately
Connect your documents as a private knowledge base (RAG): contracts, manuals, policies — answers grounded in your material, visible only to your people.
Admin control, real accounts
Team accounts with SSO, roles and usage overview — instead of a shared password and a private-card subscription nobody governs.
An API for your tools
The same private AI behind an OpenAI-compatible API — wire it into your internal tools without sending a byte to a public provider.
Public subscription vs. your private AI
| Public AI subscriptions | ATAILA private ChatGPT | |
|---|---|---|
| Where your prompts go | To a US provider’s cloud, under their terms | To private EU GPUs operated for you — they never leave the platform |
| Who learns from your data | Policy-dependent, changes over time | No one — open-weight models, no third-party training, ever |
| The bill | Per seat and/or per usage, moves as you grow | Flat monthly fee — use it like a tool, not a taxi meter |
| Your documents | Uploaded into someone else’s service | Indexed into your private knowledge base, on the platform |
| Who answers when it breaks | A ticket queue | The team that operates it — under a written SLA |
From €500 / month, net of VAT — the operated tier, with your knowledge base included. How pricing works →
Straight answers
- Which models will we get?
- A menu of leading open-weight models (chat, coding, vision), updated monthly as the field moves — served privately, so switching models never means switching providers.
- How private is it, really?
- Prompts, documents, logs and embeddings stay on the platform, on EU infrastructure, with no US processor in the path. That’s the difference between a privacy policy and an architecture.
- Can it answer from our documents?
- Yes — the operated tier includes a private knowledge base (RAG) built from your files, so answers cite your material instead of guessing.
- How fast can the team start?
- Days, not months: accounts and SSO first, your knowledge base next. Most teams send their first prompts the week the contract is signed.
End the shadow-AI trade this month.
Tell us how many people need a seat and what your data rules are — you’ll get a written quote and a rollout plan.