Your IDE is Evolving.
Meet AIDE.

AIDE is the AI Integrated Development Environment. Your IDE handles code. AIDE by RocketRide handles everything that comes after: the models, pipelines, memory layers, guardrails. The answer at 3am when something breaks.

Open source | Any model | Built for production

Open Source from
‍day one

The AI landscape shifts every six months. AIDE gives you a stable, open foundation to compose, swap, and control your stack without rewrites. Open source because infrastructure this critical cannot be a black box.

@rocketride

Visual
Pipeline Builder

Drag and drop nodes to compose any model, vector store, processor, or agent into a working pipeline. Visual, real-time, and yours to control.

Docker
Deployment

Build an image for your workflow, then generate a run script. Copy the output to your server and start it with one command.

AIDE is not just for building. It runs in production.


# Build (in repo dir on your server)
docker build -f docker/Dockerfile.engine -t rocketride-engine .

# Run on your server
docker run -p 8080:8080 rocketride-engine

Everything
in AIDE

Build, run, update, maintain, and control your AI solutions, all in one environment. The full lifecycle, not just the first step.

One Click
Cloud Deploy

Go from local runs to cloud deployment in one click, with the same settings.

Local Dev
Localhost: 3000

Coming Soon

RocketRide Cloud
api.rocketride.io

One-click deploy

Live

Multi Agent
Workflow

Any model, any tool, any framework via MCP or Python nodes. When a better one ships, swap it in. Model-independence is not a feature. It is a right.

A Simple SDK for
‍Real AI Solutions

Integrate AI pipelines you build and deploy into applications, workflows, and automations with Python or TypeScript.

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())