Private AI workspace
Self-Hosted AI Workspace
A complete, operator-controlled AI workspace for teams that need private models, governed tools, durable workflows, and visible operations.
Key considerations
Private by deployment
Run the application and its data services inside infrastructure your team controls.
One operating surface
Bring chat, scheduled work, repository tasks, media, assets, tools, and administration together.
Runtime choice
Connect vLLM, LM Studio, Ollama utility models, and ComfyUI according to workload and environment.
Architecture at a glance
More than a private chat interface
Pulsar is designed around the work teams perform after a model is connected. Conversations, recurring tasks, generated media, repository-aware coding work, saved outputs, tools, and administration use one product language and one operator-owned deployment.
- Chat keeps conversations, attachments, tool context, and sharing controls together.
- Scheduler runs one-time or recurring chat, Starbuck, and monitoring tasks with visible history.
- Library retains generated and uploaded work so evidence remains findable.
Control stays with the operating team
The public-cloud model is not assumed. Teams decide where the application runs, which model endpoints are permitted, how services are exposed, and which capabilities are available to users.
- Application services can remain behind a reverse proxy and controlled network boundaries.
- Operators manage users, product capabilities, runtime endpoints, queues, storage, diagnostics, and audit history.
- Higher-risk writes, repository changes, package work, and administrative actions remain explicit and reviewable.
Choose runtimes by responsibility
Pulsar separates the user workspace from the underlying inference and media services. That makes it possible to use a production GPU runner for chat, a smaller local endpoint for evaluation, a CPU utility model for internal tasks, and a dedicated media workflow host.
- vLLM fits GPU-backed, OpenAI-compatible production inference.
- LM Studio fits local labs, evaluation, and smaller deployments.
- Ollama can remain internal-only for titles, summaries, diagnostics, and prompt optimization.
- ComfyUI powers image and video workflows under operator-managed model and queue policy.
Designed for evidence and recovery
A private AI workspace still needs operational discipline. Pulsar exposes service health, queues, diagnostics, storage, runtime state, and known-safe recovery paths so teams can understand failures without handing control to a hosted vendor.
- Visible health and dependency status.
- Durable job queues with bounded retries.
- Admin audit history and reauthentication for sensitive operations.
- Safe recovery actions rather than arbitrary model-driven infrastructure access.
Where Pulsar fits
Pulsar is a strong fit when an organization needs AI capabilities but must retain deployment ownership, model choice, data locality, and operating visibility. Teams seeking a zero-operations hosted chat subscription may prefer a managed service; Pulsar is intentionally built for organizations prepared to own or partner on the environment.
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.