Add remote execution to Flowise workflows

Flowise gives you a visual layer for assistants, chatflows, and agent workflows.

Jungle Grid runs the heavy job and returns job lifecycle data to the flow.

Useful when a Flowise workflow should submit a tracked remote job through HTTP or a custom tool.

User / Agent / Workflow

A user action or system event starts the process that needs remote AI execution.

Integration tool

The orchestration layer validates input, manages state, and decides when a remote job should run.

Jungle Grid API

The workflow layer submits a workload request and receives a tracked job identifier back.

Remote AI workload execution

Jungle Grid handles placement, execution, provider capacity, and lifecycle control for the job.

Status + logs + result

The integration layer polls state, reads logs, and collects result payloads or failure reasons.

App / Agent / Workflow

The original system turns job state and outputs into the next user-facing or automated step.

A Flowise chatflow or agentflow receives a request from the user.

A custom tool or API node decides a remote AI workload should be launched.

The node submits the job to Jungle Grid.

Flowise displays status, logs summaries, or progress while the workload runs remotely.

The workflow reads the final result and continues the visual flow once Jungle Grid completes the job.

const response = await fetch("/api/junglegrid/jobs", {
  method: "POST",
  headers: {
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    workload: "inference",
    model_size: 7,
    image: "your-image:latest",
    command: "python run.py"
  })
});

const job = await response.json();

const statusResponse = await fetch("/api/junglegrid/jobs/" + job.id);
const status = await statusResponse.json();

Visual AI workflows that need to trigger tracked remote jobs instead of keeping all work inside the builder runtime.

Assistant or chatflow experiences that should expose logs, status, and result state from a remote execution layer.

Prototype and production flows where developers want a clear separation between orchestration UX and compute execution.

Do I need a custom Flowise node to use Jungle Grid?

Not necessarily. An HTTP or API node can be enough for many cases, though a custom tool node may give a better developer experience if Jungle Grid becomes a common execution target in your flows.

Should Flowise run the heavy AI job directly?

Usually no. Flowise is a stronger fit for visual orchestration and tool logic. Jungle Grid should handle heavier remote execution when the job needs tracked runtime behavior.

Can a Flowise UI show status and logs from Jungle Grid?

Yes. The flow can store the returned job ID, poll Jungle Grid, and surface status, logs summaries, and final results back into the visual workflow or UI.

Next step

Keep Flowise visual and Jungle Grid execution-focused

Use Jungle Grid as the remote execution backend behind Flowise so the workflow builder stays focused on visual orchestration instead of infrastructure management.