Mustashar · On-premise LLM
A private LLM on your own servers, with the assistant your teams expect.
Mustashar runs open large language models in your data center, your private cloud or a UAE cloud we run for you. It answers from your documents with citations to the page, follows your access rules and works in Arabic and English. Your data never trains public models.
- Open models on your servers
- Answers cited to your documents
- Arabic and English
Birbal Assistant
Private · on your serversYou
What is the notice period for contractors?
Assistant
Contractors need 30 days’ written notice, unless their contract says otherwise.
You
ما هي سياسة العمل عن بُعد؟
Assistant
يُسمح بالعمل عن بُعد يومين في الأسبوع بموافقة المدير المباشر.
Authorized vendor to
- Ministry of Finance
- Ministry of Interior
- DGE Abu Dhabi
- Etihad Aviation
- EDGE Group
Delivered for
- Hindustan Unilever
- Nokia
- Linde
- USA Today
- JSL
Procurement-ready
- Emirati national company
- National ICV certificate
- Abu Dhabi Government Procurement Gate
- UAE Ministry of Finance, federal procurement
- Registered ADNOC vendor
Why on-premise
Why organisations run their own LLM
An on-premise LLM runs on servers you control, instead of a provider's cloud service.
Data that can't leave
Contracts, case files and citizen data stay on infrastructure you control.
Answers from your own documents
The model answers from your files and systems and shows the page each answer came from.
Your choice of models
Use open models on your servers or cloud models you approve, and change them later without rebuilding.
What you get
More than a model on a server
A model alone doesn't make an assistant. Mustashar adds what teams need around it.
Ask your documents
Answers grounded in your files, with citations to the exact page.
Access follows permissions
People only get answers from documents they're allowed to open.
Connectors to your systems
SharePoint, Google Drive, SAP, Oracle and CRMs, through connectors we build.
Agents that do the work
Draft letters, summarise cases, fill forms and update systems, with approvals.
Arabic first
Search, chat and summaries in Arabic and English, including mixed documents.
Admin and audit
Usage analytics, conversation logs and retention controls for IT and compliance.
On-premise vs cloud
Mustashar on your servers vs ChatGPT Enterprise
ChatGPT Enterprise facts come from OpenAI's own pages, checked on 14 November 2026. Both can keep data in the UAE; the difference is who runs the system and where.
| What you get | Mustashar | ChatGPT Enterprise |
|---|---|---|
| Where it runs | Your data center or private cloud, or a UAE cloud region we run for you | OpenAI's cloud |
| Data at rest | Stays on the servers you choose | New Enterprise workspaces can store content at rest in the UAE or nine other regions |
| Model processing | On your servers, or with cloud models you approve | UAE inference residency for eligible workspaces, with selected models; OpenAI says some non-GPU processing may still happen globally |
| Models | Open models of your choice, switchable without rebuilding | OpenAI's models |
| Your documents | Connectors we build to SharePoint, Google Drive, SAP, Oracle and CRMs, with your access rules | Company knowledge through connected apps; data residency support differs by app |
| Getting started | A 14-day pilot with one team, then a written quote | Data residency included at no extra cost on Enterprise |
Getting started
From pilot to every department
- 01
Choose a team
Pick one department and its key documents for the pilot.
- 02
Choose where it runs
Your servers or private cloud, or a UAE cloud region we run for you.
- 03
Connect sources
We connect file stores and systems with your access rules.
- 04
Pilot for 14 days
Users ask real questions; we measure answer quality and time saved.
- 05
Roll out
Expand to more teams and add agents for repeat tasks.
Sources
Where the ChatGPT Enterprise facts come from
OpenAI's own pages, checked on 14 November 2026. Products and regions change, so check the current pages before you decide.
14-day pilot
Start a 14-day private pilot
We set up a private assistant on one team's documents, on infrastructure you choose. At the end you get a report on answer quality and time saved.
- Your data stays in your environment
- A report on answer quality and time saved
- Clear pricing before any rollout
4.9/5 average rating · 98% client satisfaction · 150+ clients served
FAQ
On-premise LLM: questions buyers ask
What is an on-premise LLM?
A large language model that runs on servers you control, in your own data center or private cloud, instead of being used as a provider's cloud service. Your prompts, documents and answers stay on that infrastructure.
What is a private LLM?
A language model your organisation runs for its own use, on infrastructure it controls or a dedicated environment, so its data isn't shared with a public AI service. Mustashar is a private LLM platform: the models, your documents and the assistant all run where you choose.
What is the difference between on-premise and hosted AI?
With hosted AI, the provider runs the models and stores your data in its cloud, sometimes in a region you choose. With on-premise AI, the models run on your own servers, and your team or a partner like us operates them.
Which models can Mustashar run?
Open models hosted on your infrastructure, or cloud models you approve. You can change models later without rebuilding.
What hardware do we need?
It depends on the models you choose, the number of users and how quickly answers must come back. We work this out with you before installation, and the 14-day pilot can run on infrastructure you choose.
Is ChatGPT Enterprise available with UAE data residency?
Yes. According to OpenAI, eligible new ChatGPT Enterprise workspaces can store content at rest in the UAE, and eligible workspaces can add UAE inference residency for selected models. It still runs in OpenAI's cloud. Mustashar runs on your own servers or in a UAE cloud region we run for you.
Does our data train the AI?
No. Your documents and conversations are never used to train public models.
Run your own LLM, with answers your teams can trust
Start with one department in 14 days.
Start a pilot