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AI for healthcare teams, reviewed before it spreads.

Care teams, researchers, and administrators are already looking for AI help with notes, policies, documents, and internal knowledge. Open WebUI gives them an approved workspace your privacy, security, and informatics teams can configure, inspect, and govern.

Review enterprise docs Review governance materials
Care setting
Offer approved AI assistance inside the hospital, clinic, payer, research, or administrative environment you govern.
Sensitive work
Keep prompts, uploaded files, knowledge sources, retention, and model routing aligned to your review process.
Team access
Map SSO, groups, and role-based access control to care teams, operations, research, and administration.
Privacy review
Give privacy, security, and informatics teams one place to review usage, access, and configuration.

"Trust is not a checkbox. It is the quiet work of deciding what belongs in an assistant, who should use it, what it may reach, and when a helpful shortcut has become a clinical process. Healthcare needs useful AI that earns review."

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Healthcare AI has to fit the way care actually works.

01
Where it runs

Deploy Open WebUI in the environment your organization already governs: hospital infrastructure, private cloud, research network, or another restricted setting. Use Docker, Kubernetes, or your existing deployment process.

02
What teams can use

Give each group access to the models, knowledge collections, tools, and workflows they are approved to use. Care operations, research, revenue cycle, and support teams do not need the same configuration.

03
How it is reviewed

Keep identity, permissions, retention, audit, and administrator review close to the people responsible for privacy, security, informatics, and compliance operations.

The pressure is not theoretical.

Teams ask for help with

Policy questions, prior internal notes, organizational knowledge, research, forms, and operational writing.

Leaders need to know

Which tools are being used, what data they can touch, who has access, where records sit, and how outputs are reviewed.

When that work moves into personal accounts and unreviewed tools, AI becomes hard to see exactly when healthcare organizations need the most visibility.

Open WebUI gives healthcare teams an approved place to start.

Bring AI into a workspace your organization operates. Connect approved models, publish reviewed knowledge, assign access by team, and keep administration close to the people responsible for privacy, security, and clinical informatics.

Start with approved use

Pilot internal knowledge, policy search, summarization, research support, and operational workflows before expanding access.

Route by policy

Connect local, private, or hosted models and expose them only where evaluation and policy allow.

Review in one place

Manage access, knowledge, tools, model visibility, retention, and review without scattering AI usage across ad hoc tools.

Useful AI in healthcare lives in ordinary workflows: rounds, handoffs, policies, research, internal documentation, and administrative work. The workspace has to meet those teams where they already are.

Materials for privacy, security, and informatics review.

Before a healthcare AI pilot expands, reviewers need to understand where the system runs, how access is assigned, how data is stored, which models are available, and how the deployment maps to safeguard expectations.

Enterprise security Data privacy & encryption Authentication & access Hardening baseline Deployment patterns HIPAA Security Rule Covered entities & business associates
Get started

Start with a workspace your teams can review.

$ pip install open-webui

One command. 60 seconds. No account required. Run it with Docker, Kubernetes, or your existing deployment process.

Contact enterprise sales

Healthcare AI, answered.

Where does Open WebUI fit in a health system?
Open WebUI is the AI workspace layer. It gives teams a place to use approved models, knowledge, and tools while your organization controls deployment, identity, access, storage, and routing. It can support internal workflows such as policy search, operational drafting, research assistance, administrative documentation, and knowledge access, depending on what your review process approves.
Does Open WebUI handle HIPAA for us?
No software product handles HIPAA obligations by itself. A healthcare compliance posture depends on the covered entity or business associate, the use case, safeguards, policies, procedures, risk management, workforce controls, contracts, and operations. Open WebUI can support that work by letting you self-host, control model routing, map access to identity groups, and keep audit and retention in systems you administer.
What happens to chats and uploaded files?
In a self-hosted deployment, chats, files, knowledge bases, embeddings, users, permissions, and logs are stored in the database and storage you configure. Data is not sent to Open WebUI as a managed service. It is routed to external systems only when you configure an external provider, tool, model endpoint, or integration.
Can different teams use different models?
Yes. Open WebUI can connect to local engines such as Ollama, vLLM, any OpenAI-compatible endpoint, private endpoints, and hosted providers. Administrators can decide which models are visible to which users or groups, so teams can evaluate and use models according to their role, workflow, and policy.
How does this fit PHI workflows?
Open WebUI gives teams a centrally managed workspace where access, knowledge sources, model visibility, tools, and administrator review can be configured together. For workflows involving protected health information, your organization still needs to decide what data may be used, who may access it, how long it is retained, which systems may receive it, and what safeguards are required.
Is this for clinical decision-making?
Open WebUI is a workspace for interacting with AI models and tools you configure. It is not a medical device, does not provide independent clinical judgment, and should not be used as the sole basis for diagnosis, treatment, or clinical management. Healthcare organizations should evaluate each model, workflow, and output standard before using AI in clinical contexts.