AI for your team. In an environment you control.
Give your team a place to research, write, analyze documents, and work with AI on your own infrastructure. Bring your knowledge and tools into the same workspace, and make useful assistants available to the people who need them.
Open WebUI gives you the workspace and the freedom to shape it. You choose where it runs, who can access what, and which models and services it uses. Your team can put AI to work in an environment your organization manages.
Make it your organization’s workspace.
Run Open WebUI in your own cloud or on premises. Connect internal knowledge and systems, set up access for your teams, and choose the capabilities available to them. Keep the models that work for you and add others as your needs change.
Open WebUIYour organization’s AI workspace.Control includes the connections you enable. External models and tools can receive the data sent to them. For work that must stay internal, configure and test the full processing path within your environment. Explore AI on your own infrastructure.
Put that workspace to work.
Work with the knowledge you already have.
Ask questions about documents, research with connected search tools, and turn what you find into a draft or analysis. Bring your own reference material into the work, with shared collections available to the right people.
Build assistants around your work.
Combine instructions, knowledge, and tools into an assistant for a recurring task. Prepare a research brief in your team’s format or connect an assistant to an internal service. Share it with colleagues and improve it as you learn.
Give people a place to work together.
Develop ideas in shared channels with colleagues and AI. Keep drafts in notes and share useful prompts, knowledge, and assistants. Teams can build on each other’s work within a workspace your organization operates.
Open WebUI is free to use as-is with its branding intact under its license. Budget for hosting, model usage, and the people supporting the workspace. For enterprise licensing and support, talk to our team about your requirements.
See how teams use Open WebUI.
From internal research to everyday operations, teams are making Open WebUI their own.
These are published customer experiences. Use them as context for your evaluation; your requirements, configuration, and results will differ.
Start where you are.
You might be proposing a useful workflow for your team or bringing an organization-wide AI strategy into practice. Start with the help you need: make the case, try it on real work, or prepare your rollout.
AI on your terms.
Your models. Your data. Your infrastructure.
Questions, answered.
Do we need to replace our existing models?
No. Start with the approved model endpoints that serve your work today. Open WebUI is the workspace around those models. Local inference and hosted APIs can be part of the same deployment; provider capabilities and terms still apply.
Does self-hosting mean we need our own GPUs?
Only if you choose to run models on your own hardware. Hosting the Open WebUI application and serving model inference are separate decisions. You can operate the workspace while connecting to approved hosted model APIs.
Will all our data stay inside our network?
That depends on your configuration. Connected model APIs, embedding services, search providers, tools, and other integrations may receive data. Map the full request path, including storage and logs. An internal interface alone does not make every connected service internal.
What should we budget for?
Open WebUI is free to use as-is under its license. Budget for model usage or inference hardware, application hosting, storage, backups, administration, and user support. Enterprise services, such as custom branding or a formal support agreement, are optional and priced separately.