RocketRide is the open source AIDE: the AI Development Environment.
Build, deploy and harness production-ready AI solutions at light speed, all within your IDE or using the CLI in your terminal.
Your code editor just became the AIDE. RocketRide turns the classic IDE you already use into a full AI Development Environment: one place to compose, debug, observe, and deploy AI runtimes using any model, any tool, any framework, with zero vendor lock-in. Equipped with deep observability and backed by a battle-tested, high-throughput C++ engine, what you build is production-ready the moment it runs. It's the harness for everything behind your AI applications, not just the agents, but the whole stack beneath them.
Under the hood, RocketRide is an open source data pipeline builder and runtime built for AI and ML workloads. With 50+ pipeline nodes spanning 13 LLM providers, 8 vector databases, OCR, NER, and more, pipelines are defined as portable JSON, built visually in VS Code, and executed by a multithreaded C++ runtime. From real-time data processing to multimodal AI search, RocketRide runs entirely on your own infrastructure.
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_Design, test, and ship complex AI workflows from a visual canvas, right where you write code._
_Drop pipelines into any Python or TypeScript app with a few lines of code, no infrastructure glue required._
## Two ways to run RocketRide
_Let us handle the infrastructure, or own every layer._
ROCKETRIDE CLOUD · NOW LIVE |
ON-PREM |
| Let us run it, zero ops The fastest way to get started. We operate the engine; you point a client at the endpoint and build. The same .pipe file runs unchanged, with no infrastructure to provision, from prototype to production. |
Run it yourself, free Docker, on-prem, or local. Full control and data residency. Open source, MIT, no lock-in, ever. |
| Get Started | Quick Start |
NOW LIVE
With RocketRide Cloud, offload the complex, heavy lifting of production AI.
Build your pipeline once, in the same portable .pipe format, and we run it, scale it, and keep it fast. No servers, no ops, no rewrite from prototype to production.
| A fraction of the cost Our patent-pending model server runs your AI workloads far more efficiently, so you pay a fraction of what standard hosting costs. |
Collaborate as a team Work together on shared pipelines. Your whole team builds, runs, and iterates in one place. |
| No-hassle infra We handle everything: servers, scaling, upgrades, uptime. Nothing to provision, nothing to operate. |
Higher performance, built-in scale More throughput on the multithreaded C++ engine, with automatic scalability built in. |
Get Started · Read the Cloud docs
## On-PremFREE & MIT
Run the very same engine yourself, wherever your data lives.
Docker, on-premises, or a local process in your IDE. Full control, full data residency, and zero lock-in. The exact .pipe you build on Cloud runs unchanged on your own hardware.
| Full control and data residency Your data and model calls never leave your infrastructure. Run it behind your firewall, or fully air-gapped. |
Open source, MIT The whole engine is MIT-licensed and OSI-compliant. No enterprise edition, nothing behind a paywall. |
| Runs anywhere Docker, on-premises, bare metal, or local. Scale out to a cluster with the Helm chart when you need to. |
The same C++ engine Identical multithreaded runtime and execution semantics as Cloud. Move a pipeline between them anytime. |
Quick Start · Read the On-Prem docs
## Features | Feature | Description | | :-------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Visual Pipeline Builder** | Drag, connect, and configure nodes in VS Code, no boilerplate. Real-time observability tracks token usage, LLM calls, latency, and execution. Pipelines are portable JSON, version-controllable, shareable, and runnable anywhere. | | **High-Performance C++ Runtime** | Native multithreading purpose-built for the throughput demands of AI and data workloads. No bottlenecks, no compromises for production scale. | | **85+ Pipeline Nodes** | 13 LLM providers, 8 vector databases, OCR, NER, PII anonymization, chunking strategies, embedding models, and more. All nodes are Python-extensible, build and publish your own. | | **Multi-Agent Workflows** | Built-in CrewAI and LangChain support. Chain agents, share memory across pipeline runs, and manage multi-step reasoning at scale. | | **Coding Agent Ready** | RocketRide auto-detects your coding agent: Claude, Cursor, and more. Build, modify, and deploy pipelines through natural language. | | **TypeScript, Python & MCP SDKs** | Integrate pipelines into native apps, expose them as callable tools for AI assistants, or build programmatic workflows into your existing codebase. | | **Zero Dependency Headaches** | Python environments, C++ toolchains, Java/Tika, and all node dependencies managed automatically. Clone, build, run, no manual setup. | | **One-Click Deploy** | Run on Docker, on-prem, or [RocketRide Cloud](https://cloud.rocketride.ai/). Production-ready architecture from day one, not retrofitted from a demo. | ## Quick Start 1. Install the extension for your IDE. Search for RocketRide in the extension marketplace:
Ready to ship? Deploy your pipeline on RocketRide Cloud, or run on-prem, free.
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