Your IDE is evolving. Build faster with RocketRide.

From prototype to production, with the tools AI teams actually need.

‍Open source | Any model | Built for production

Open source.
‍Built to adapt.

AI moves fast. RocketRide gives you the flexibility to adopt new models,
tools and workflows without rebuilding what you’ve already created.

@rocketride

Go from idea to pipeline. Fast.

Drag and drop models, vector stores, processors, agents, and more onto the canvas. Connect them visually to build complex AI workflows and see the full pipeline in real time. Start from a template or blank canvas and go from idea to running in minutes. Ships with ready-to-use agent instructions for Cursor, Claude Code, Windsurf, and Copilot. Your coding agent knows the framework out of the box.

Real observability,
from data chunk to deployment.

See data flow through every node in real time. Trace a failure down to the exact data chunk, call, and duration. Track token spend, CPU, GPU, and memory as pipelines run. Server-level monitoring shows all running tasks, connections, and activity in one view.

Works where you already are.

The VS Code Extension upgrades your IDE for the AI-native era, adding the runtime, orchestration, and observability layer it was never built for. For CLI developers: Python and TypeScript SDKs and MCP Server have you covered.

One click. Total control.

One click from development to production with RocketRide Cloud. Or self-host perpetually, for free, on a dedicated server, Dockerized, or locally. No lock-in. Your choice, always.

Deploy on RocketRide Cloud

Fully managed AI infrastructure with predictable costs and true portability. Move from prototype to production without compromise.

Any model. Any tool.

Any model, any agent, any framework. Automatically route prompts to the best model at runtime. When a better one launches, swap it in without rewriting your pipeline. Today’s best model is tomorrow’s legacy code.

Lines of Code

689

123

82% less

Concurrent Data Loss

Up to 84%

0%

Concurrency Code

14–17 lines custom Python

0 lines

Crash Isolation

Failure can interrupt the wider batch

Failure contained by default

64-Document Stateful Job

Failed under stateful workload

Completed successfully

View full benchmark repo →

IDE or CLI?
‍Yes.

Work your way. Build and manage AI pipelines from your IDE, CLI, or both.

TypeScript SDK



import { RocketRideClient } from 'rocketride';

const client = new RocketRideClient({
  uri: 'http://localhost:5565'
});

await client.connect();

const { token } = await client.use({
  filepath: './pipeline.json'
});

const result = await client.send(
  token,
  'Hello, pipeline!',
  { name: 'input.txt' },
  'text/plain'
);

console.log(result);

await client.terminate(token);
await client.disconnect();

Python SDK



import asyncio
from rocketride import RocketRideClient

async def main():
    async with RocketRideClient(uri="http://localhost:5565") as client:
        # Run a pipeline
        result = await client.use(filepath="pipeline.json")
        token = result["token"]

        # Send data into the pipeline
        response = await client.send(token, "Hello, RocketRide!")

        # Check pipeline status
        status = await client.get_task_status(token)
        print(f"State: {status['state']}")

asyncio.run(main())