Run AI on
hardware you own.
Open models. Private workflows. Your infrastructure. Software and services for a more independent way to work with AI.
In development. Built for the local-first future.
Demo: simulated responses, nothing leaves your browser
A local stack.
A world of possibilities.
From your first offline conversation to private team infrastructure. Meet the tools we’re building.
LOCAL AI Studio
A desktop app to run open models offline. A calm workspace for prompts, experiments and everyday thinking.
Explore Studio On-prem · Coming soonLOCAL AI Server
Self-hosted inference for teams. Keep the runtime on your infrastructure and make local models available on your terms.
Explore Server Runtime · Coming soonLOCAL AI Agents
A local agent runtime designed for explicit tools, clear permissions and work you can inspect.
Explore Agents Catalog · Coming soonLOCAL AI Hub
A catalog of open models with licence context. Explore what fits your task, hardware and intended use.
Explore HubA shorter path from
open model to useful work.
Find your model.
Start with a task, then consider the model’s licence and hardware needs. Keep the choice in your hands.
Bring it home.
Set up a runtime on your machine or your team’s infrastructure. Download what you need, then work locally.
Make it your workflow.
Chat, evaluate and connect approved tools. Move from experiments to workflows you can understand and maintain.
Keep your work
inside your walls.
Local inference gives you a practical data boundary. The rest takes thoughtful engineering.
- Run prompts and inference on hardware you control.
- Choose where models and conversation files live.
- Review permissions before connecting agents and tools.
From “could we?”
to a clear deployment plan.
Setup & hardening
Choose a suitable runtime, establish safe defaults and document the boundaries of your local AI environment.
On-prem deployment
Plan private inference around your network, hardware, access policies and operational responsibilities.
Model evaluation
Compare candidate models against your real tasks, licence requirements and data-handling constraints.
Training for teams
Help your people understand local AI, review model output and build repeatable, responsible workflows.
Local or cloud?
Start with what matters.
Both have a place. Choose around your data, your operations and the work you need to do.
| Consideration | Local AI | Cloud AI |
|---|---|---|
| Data boundary | Infrastructure you control | Provider-managed infrastructure |
| Connectivity | Offline-capable after setup | Typically needs a connection |
| Model choice | Models your hardware can support | Models the provider offers |
| Operations | You manage updates and capacity | Provider manages the runtime |
| Best fit | Control, customisation, private workflows | Managed access, elastic workloads |
A future community and incentive layer for shared local compute, open models and local-first apps. Planned ticker: $LOCALAI. The coin is not issued.
Meet the ecosystemYour AI. Your hardware.
Your next move.
Help shape LOCAL AI. Tell us what you want to run.