Build a shared AI video live stream for an audience
Stream one generated AI video session to authorized viewers. Design host controls, audience input, session ownership, billing and recording boundaries.
A shared AI video experience runs one model session and delivers the same generated state to several authorized viewers. On Windflow, additional viewers of that session do not add a second ready-time meter. Separate independently generated sessions are metered separately.
This pattern fits host-directed stories, group world exploration and interactive demos. It is useful when an audience should influence or watch the same experience rather than each viewer navigating a different scene.
Separate ownership, viewing and control
The owner creates and ends the session. Viewers receive authorized access to its generated tracks. Your application decides who can request a control and how competing requests are resolved.
Do not distribute an owner credential to every viewer. Use a backend that authenticates audience members and grants only the required access. Keep account API keys on the server and validate requests that consume model capacity or change the experience.
Give the audience one coherent input policy
| Audience pattern | Control policy | Model to evaluate |
|---|---|---|
| Watch a host direct a scene | Host alone sends controls | Helios, LongLive 2.0 |
| Vote on the next story choice | App collects votes and sends one chosen instruction | LongLive 2.0 |
| Watch a group explore a world | One selected controller sends movement and look | LingBot-World |
| Watch generated video with sound | Host controls generation at supported boundaries | LTX-2.5 |
These are application designs, not built-in voting or moderation features. Sending every audience action directly to the model can create conflicts and unpredictable scenes. Keep turn-taking and input validation in your application.
Build the event lifecycle
- Arrange access and verify capacity before the scheduled event.
- Create the owner session, show queueing state and confirm generated output.
- Issue authorized viewer access through your backend.
- Stream the generated track and expose only the intended audience controls.
- Handle host disconnects with an explicit reconnect or end policy.
- Release the owner session when the event ends, even if viewers leave earlier.
Windflow is in private beta with on-demand capacity. A model being listed as production does not establish reserved capacity for your event. Discuss workload and readiness before inviting an audience.
Plan recording and delivery separately
A live generated track and a durable exported recording have different lifecycles. Make recording an explicit action and explain retention to users. Windflow's temporary recordings expire after 24 hours during private beta; high-volume exports, storage or private delivery require a scoped discussion.
For wider distribution, decide how viewers are authorized and how media reaches them. The transport guide explains the direct session delivery options; audience fan-out at event scale should be evaluated for the intended workload.
Estimate cost correctly
Use the selected model's ready-second rate and the event's session duration. Do not multiply that generation meter by the number of viewers sharing the same session. Do multiply by independent owner sessions if you run several scenes at once.
A ready session can remain billable while video delivery is paused or no viewer remains. Ownership and release policy control that risk. See pricing and the per-second billing guide.
FAQ
Does each viewer add another generation charge?
No. Windflow meters one shared owner session once, regardless of the authorized guests receiving it. Independent sessions have their own meter and reservation.
Can every viewer explore a different world in one session?
No. A shared session has one generated state. Independent worlds require independent sessions.
Does a shared session provide an audience voting system?
Your application implements voting, moderation and control ownership. It then sends the selected, supported command to the model.