On-premise AI means your AI agents and language models run entirely on your own hardware - inside your building, on your GPUs, behind your firewall. No data ever leaves your network. Inwizards builds, deploys, and maintains private AI systems using open models like Llama and DeepSeek.
Both are right. Nearly every AI platform on the market is cloud-only - your documents and customer records flow to someone else's servers. Almost nobody builds custom AI that runs inside the client's own infrastructure. That is exactly what Inwizards does: the full AI stack, deployed on your GPUs, behind your firewall.
Client records, transactions, and deal data stay inside the bank - AI assistants your risk and compliance teams can actually sign off on.
Patient data never touches an outside API. Private assistants for records search, clinical notes, and admin - inside your own network.
Citizen data and internal documents stay on infrastructure you control - with air-gapped deployment where policy requires it.
Privileged client files stay privileged. AI for research, drafting, and document review that never leaves the firm.
GDPR and the EU AI Act make "where does the data go?" a board-level question. On-premise is the clearest answer: it goes nowhere.
AI agents for EuropeContractors, R&D teams, and manufacturers whose designs are the business. Fully isolated AI with zero external calls.
Everything below runs inside your network. "Open models" are AI models whose weights you can download and run yourself - no vendor lock-in, no per-question fees to a cloud provider.
Llama 3.x, DeepSeek, Mistral, and Qwen - proven open models we select, deploy, and tune for your use case. You own the deployment outright.
Models served with vLLM and Ollama - the engines that make open models fast enough for real daily work on your own GPUs.
Retrieval-augmented generation: the AI answers from your files, wikis, and records using a local vector database - the documents never move.
Agents orchestrated with LangChain, LangGraph, and CrewAI that search, draft, and update your systems - all inside your firewall.
AI agent developmentLoRA fine-tuning - a lightweight way of training - teaches the model your domain language and formats. Training runs on your hardware too.
For maximum-security environments, the entire stack runs with no internet connection at all. Updates arrive by controlled transfer.
Every piece below is open or self-hosted - it runs where your data lives.
On-premise AI runs on NVIDIA GPUs - graphics processors that happen to be very good at running AI models. You do not need a data center to start.
The right hardware depends on the model size and how many people will use it - and buying wrong is expensive. So we assess first, recommend second, and you purchase only what your workload actually needs.
One GPU machine on a desk can run a capable private assistant for a team.
For larger models and company-wide use, a dedicated GPU server sits in your server room or private data center.
We size your workload and recommend exact hardware - so you never overspend on GPUs you do not need.
Not every company needs on-premise. If you do, you already know why. Here is the trade-off, honestly.
| Cloud AI | On-Premise AI with Inwizards | |
|---|---|---|
| Where your data goes | Leaves your network for the provider's servers | Stays on your hardware - nothing leaves |
| Getting started | Faster - sign up and go | Slower - hardware is scoped and installed first |
| Cost model | Per-use fees that grow with usage | Hardware you own once, plus a scoped build |
| Hardware needed | None | NVIDIA GPUs - we scope them before you buy |
| Compliance & residency | Depends on the provider's terms and regions | Your building, your rules - air-gap available |
| Model quality | Frontier models lead open-ended reasoning | Open models - strong on focused tasks with RAG and fine-tuning |
| Who controls it | The provider | You own it - we build, maintain, and train your team |
Honest answer: if your data is allowed to live in the cloud, cloud is simpler - start with our AI agents platform or hosted AI agents. If it is not allowed to leave, we build the alternative almost nobody else offers.
A phased approach that proves value before you invest in hardware.
We map your use case, data, and compliance rules - and scope the exact hardware before you buy anything.
We prove value on a single focused use case first, so you commit to hardware with evidence, not hope.
We install the full stack - model, RAG, agents - on your GPUs, inside your network.
Your people learn to run, use, and extend the system. You own it - no lock-in, not even to us.
We monitor, patch, and upgrade to better open models as they ship - on your schedule, in your network.
Offices in the US, UAE, and India - custom software since 2004.
Figures reflect Inwizards' company history and platform capabilities.
Straight answers on cost, hardware, quality, and privacy.
Book a discovery call. We'll map your highest-value private AI use case, scope the exact hardware, and give you a fixed pilot plan - before you buy a single GPU.
✓ NDA & IP yours · ✓ Hardware scoped before you buy · ✓ Air-gap option
Tell us what you want AI to do and what your data rules are. We'll come back with a straight answer on hardware, scope, and whether on-premise is right for you — usually within one business day.