Architecture comparison
Private AI Workspace vs. Hosted AI
Compare private and hosted AI workspaces across data boundaries, model choice, integrations, operations, governance, cost, and organizational responsibility.
Key considerations
Private workspace
Maximum deployment control with greater operating responsibility.
Hosted workspace
Faster adoption with vendor-owned infrastructure and boundaries.
Decision rule
Choose according to constraints, ownership, and risk tolerance.
Private is an operating model
Self-hosting is not only a data-location choice. The organization owns or delegates infrastructure sizing, monitoring, updates, backups, incident response, runtime policy, and user governance.
Hosted is a service boundary
A hosted platform can reduce time to value and operational work, but model availability, data handling, integrations, observability, and administrative controls remain constrained by the provider.
Choose Pulsar when control is a requirement
Pulsar fits teams that need private runtimes, durable workflows, repository-aware coding, governed media, retained assets, and visible operations in an environment they control.
Choose hosted when simplicity dominates
A hosted workspace may be the better choice when standard features are sufficient, data can enter the provider boundary, and the team does not want to operate application or model infrastructure.
| Decision area | Private workspace | Hosted workspace |
|---|---|---|
| Data boundary | Organization-defined infrastructure and policy | Vendor-defined service boundary |
| Model choice | Private OpenAI-compatible and media runtimes | Models selected by the hosted provider |
| Operations | Customer or deployment partner owns health and upgrades | Provider operates the platform |
| Governance | Deployment-specific roles, tools, approvals, and audit | Provider feature set and tenant policy |
| Time to start | Requires infrastructure and deployment review | Usually faster for standard use cases |
| Best fit | Sensitive data, model control, custom workflows, operator ownership | Low-operations teams with standard requirements |
Private deployment consultation
Review Pulsar against your environment.
Bring the infrastructure, security boundaries, model runners, and use cases. The Pulsar team will map the appropriate deployment path.