A self-hosted AI workspace runs on your own infrastructure. Tasks, documents, customer data and workflows stay in an environment you control. Pharen Hub is built as an open fair-code AI workspace and can run as managed cloud, self-hosted or private deployment. Whether external AI models or integrations process data depends on your configuration.
Many teams want AI without putting every operating detail into another black box. That becomes more important when the workspace contains documents, customer data, decisions, workflows and agent actions. For some teams, self-hosting is not a technical extra — it is a precondition for trust.
Why does self-hosting matter for AI?
| Concern | Why it matters | Pharen Hub direction |
|---|---|---|
| Data location | AI work can include customer data, internal decisions and sensitive documents. | Support for controlled deployments instead of only one SaaS path. |
| Technical transparency | Teams need to understand how the workspace handles data and workflows. | Open fair-code foundation that can be inspected and adapted. |
| Vendor dependency | A workspace becomes hard to leave once processes grow around it. | More operating freedom through open code and deployment choice. |
| AI control | Agents need clear boundaries, permissions and review steps. | Context, approvals and traceable workflows inside the workspace. |
If a workspace only manages to-dos, hosting matters but rarely decides the purchase. Once the same workspace connects AI agents with documents, customer data and decisions, the questions get bigger: Where does the data live? Who can audit access? Which models and providers are used? How are agent steps traced? Self-hosting gives your own team the answers to these questions.
Self-hosted does not mean everyone must run infrastructure
Not every team wants to operate servers. For some teams, managed cloud is the right start. For others, a private or self-hosted setup is required because of customer promises, internal policies or compliance expectations.
The important point is choice. A self-hosted AI workspace should not be a different product with fewer capabilities. It should follow the same operating model: team work, knowledge, data, workflows and AI agents in one context. The difference is who operates the environment — not what the workspace is for.
GDPR and data sovereignty: what self-hosting changes
Self-hosting means your workspace data stays on your own infrastructure. You decide where it is stored, who gets access and when it is deleted. That is a practical advantage for GDPR assessments. External AI models and integrations still need to be selected and reviewed for your setup.
The vendor matters too: Pharen IT GmbH is a German company based in the Leipzig region. Your contact for product, license and support is in Germany.
AI agents in Pharen Hub are designed for control as well: they work with roles and approvals. You can limit what an agent can see and do, and critical steps stay with people. Self-hosting also gives you control over the underlying workspace infrastructure.
One note for context: whether a specific setup meets all requirements always depends on how you operate it. Self-hosting does not do that assessment for you — it makes it considerably simpler, because fewer external parties are involved.
When is a self-hosted setup the right choice?
Self-hosting or private deployment becomes relevant when:
- teams have privacy, compliance or customer requirements.
- AI workflows touch sensitive documents or customer data.
- organizations want to inspect or adapt the technical foundation.
- long-term SaaS dependency is a strategic concern.
- AI agents need visible permissions, approvals and auditability.
Decision table
| Situation | Likely setup |
|---|---|
| Small team, fast start, no special infrastructure requirement. | Managed cloud can be enough. |
| Team handles sensitive customer workflows or regulated data. | Private or self-hosted setup should be evaluated. |
| Company wants to inspect, adapt or deeply integrate the workspace. | Open fair-code and self-hosting become strategic advantages. |
Frequently asked questions
What does a self-hosted AI workspace cost with Pharen Hub?
The self-hosted license starts from €20. The managed cloud has a free plan, plus Starter at €25, Team at €79 and Pro at €199 per month. Details are on the pricing page.
Is a self-hosted AI workspace GDPR-friendly?
With self-hosting, workspace data stays on your own infrastructure, and you decide where it is stored, who has access and when it is deleted. External AI models or integrations may still process data depending on your configuration, so the GDPR assessment always depends on the complete setup.
What is the difference between self-hosted and managed cloud?
The product direction is the same: one workspace approach with workflows, knowledge and agents. The difference is operations. In the managed cloud, Pharen handles hosting, updates and maintenance. With self-hosting, your IT operates the environment and carries that responsibility.
Can we start in the cloud and switch later?
Many teams start in the managed cloud because it is faster, and evaluate self-hosting once customer, privacy or IT requirements become concrete. If that is your plan, talk to us early so the requirements are considered from the start.
Terms covered in this guide
- self-hosted AI workspace
- open source AI workspace
- private AI workspace
- open fair-code AI
Continue the cluster
- From tool stack to operating system for work
- A workspace where people, knowledge and agents share the same context
- AI agents become useful when they are embedded in real work
- A self-hosted Notion alternative: what Pharen Hub does differently
Next step
If you want to check whether Pharen Hub fits your stack, talk to us about your workflow or start with the cost comparison.