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OpenEAI

Name: OpenEAI agent decision packet
Creator: OpenAgent.bot
License: BSD-3-Clause

Complete open-source hardware-software platform for real-world embodied AI from arm to VLA policy.

0.6K stars 0.0K forks BSD-3-Clause license 2026-06-04 verified

bash

# Clone both repositories
git clone https://github.com/eai-yeslab/OpenEAI-Arm
git clone https://github.com/eai-yeslab/OpenEAI-VLA
# Follow the hardware assembly guide and training recipe in each repo

Open sourceSelf-hosted

Overview

What is OpenEAI?

OpenEAI is a fully open-source hardware-software unified platform for real-world embodied manipulation. It consists of two repositories: OpenEAI-Arm, a low-cost 6-DoF desktop robotic arm with complete manufacturing files, and OpenEAI-VLA, an end-to-end vision-language-action policy trained with a two-stage recipe (large-scale pretraining + task-specific fine-tuning). The platform covers the full pipeline — hardware design, low-level control, data collection, dataset processing, VLA training, and real-time deployment.

End-to-end open-source pipeline from hardware to VLA

OpenEAI releases the complete stack: CAD files, manufacturing drawings, low-level C++ control, multi-modal teleoperation, dataset processing, two-stage VLA training, and real-time deployment.

Most embodied AI papers release only model weights or simulation code. OpenEAI lets anyone reproduce the full system.

Low-cost 6-DoF arm with 2kg payload

The OpenEAI-Arm is a desktop 6-DoF manipulator with 2kg payload capacity, significantly cheaper than Franka/UR arms while maintaining sufficient capability for VLA research.

Cost has been the primary barrier to entering real-world robotics research. OpenEAI's arm design is reproducible for a fraction of the cost of commercial alternatives.

Two-stage VLA training recipe

The VLA training pipeline uses large-scale pretraining on public robot datasets followed by task-specific fine-tuning with as few as 10-50 demonstrations.

This recipe addresses the data efficiency challenge — you get the benefits of large-scale pretraining without needing to collect millions of your own demonstrations.

Multi-modal teleoperation support

Supports GELLO (puppet), SpaceMouse (delta pose), and VR (absolute pose) teleoperation methods out of the box.

Different data collection scenarios require different teleoperation interfaces. OpenEAI covers the three most common modalities.

Install

One command to start

# Clone both repositories
git clone https://github.com/eai-yeslab/OpenEAI-Arm
git clone https://github.com/eai-yeslab/OpenEAI-VLA
# Follow the hardware assembly guide and training recipe in each repo

Use cases

What teams use it for

Reproducible VLA research

Use OpenEAI's complete pipeline to conduct VLA research on hardware that any other lab can reproduce, enabling verifiable and comparable results.

Teaching embodied AI from end to end

Build the arm, collect data, train a VLA policy, and deploy — all with open-source tools. A complete embodied AI curriculum in one platform.

Custom manipulation task development

Design a new manipulation task, collect demonstrations via VR teleoperation, fine-tune the VLA policy, and evaluate on real hardware — all within the OpenEAI framework.

Ecosystem

Tags & capabilities

botopen sourceroboticsmessagingopen sourceself hosted

Comparison

How it stacks up

Choose OpenEAI for the most complete open-source VLA pipeline

vs other open robot arms

AIRA and SO-100 provide excellent hardware but do not include a full VLA training pipeline. OpenEAI is the choice when you want hardware + training in one open-source platform.

FAQ

Questions

How much does OpenEAI-Arm cost?

The exact BOM cost is documented in the repository. It is designed to be significantly cheaper than Franka/UR arms while providing sufficient capability for VLA research.

Can I use OpenEAI-VLA without the OpenEAI-Arm hardware?

Yes, the VLA training pipeline works with any robot. Use the dataset adapters to convert your robot's data format and fine-tune the policy.

Is OpenEAI commercially usable?

OpenEAI is licensed under BSD 3-Clause, which permits commercial use with attribution.

Decision brief

Should you use OpenEAI?

JSON

Best for

Researchers needing a reproducible hardware platform for VLA research
Teams building custom robotic manipulation systems on a budget
Academics teaching embodied AI with open-source tools end-to-end

Not for

Production deployment (designed for research, not industrial use)
Researchers needing non-manipulation platforms like mobile or humanoid robots

Trust and freshness

Verified 2026-06-04
License: BSD-3-Clause
Repo: eai-yeslab/OpenEAI-Arm
Open-source signal

Deployment

self hosted, cloud

Permission surface

messages, hardware

Decision signals

Self-hostable

Agent packet

Structured decision data for OpenEAI

This packet is the compact machine-readable view agents should use before following source links or taking action.

Full JSON Agent packet Markdown brief

Capabilities

robotics, messaging

Constraints

open source, self hosted

Deployment

self hosted, cloud

Permission surface

messages, hardware

Recommended workflows

Local or private AI stack, Robotics or embodied agent workflow

Overview

What OpenEAI does

What it is

OpenEAI is a unified platform with two components: OpenEAI-Arm, a low-cost 6-DoF desktop robotic arm with complete manufacturing files, assembly guides, and a full C++/Python control stack; and OpenEAI-VLA, an end-to-end vision-language-action policy with a two-stage training recipe (large-scale pretraining + task-specific fine-tuning). The platform supports multi-modal teleoperation (GELLO, SpaceMouse, VR), LeRobot-format dataset processing, and real-time deployment via a client-server architecture.

Why it matters

Embodied AI research has been limited by two factors: the cost and complexity of robot hardware, and the fragmented nature of training pipelines. OpenEAI addresses both by open-sourcing an entire platform. A research group can build the arm, collect demonstration data, train a state-of-the-art VLA policy, and deploy it — all with publicly available code and designs. This is a model for how open-source can accelerate embodied AI research.

How to evaluate it

The hardware is a 6-DoF arm with a 2kg payload, designed for reproducibility with STEP/STL files and manufacturing drawings. Low-level control runs C++ drivers with gravity compensation and feed-forward PID tracking for smooth execution. The VLA pipeline uses dataset adapters to unify heterogeneous state/action conventions from public datasets, trains on large-scale pretraining data, and fine-tunes on task-specific demonstrations. Deployment uses a standard robot-client / policy-server ZMQ interface for streaming observations and receiving action chunks.

Facts

Known metadata and operating surface

These fields are separated from editorial interpretation so agents can reason over facts and missing checks.

Resource type bot

Category Bots

Maturity active

Difficulty Unknown

License BSD-3-Clause

Pricing open source

Verified 2026-06-04

Source confidence medium

Risk level elevated

Fit matrix

Where OpenEAI fits in an agent stack

strong

Local or private AI stack

OpenEAI has multiple signals for local or private ai stack, including matching tags, capabilities, category, or positioning.

Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
Confirm official docs, current maintenance, license, and runtime constraints before production use.

strong

Robotics or embodied agent workflow

OpenEAI has multiple signals for robotics or embodied agent workflow, including matching tags, capabilities, category, or positioning.

Separate simulator claims from hardware claims and verify safety boundaries before real-world operation.
Confirm official docs, current maintenance, license, and runtime constraints before production use.

partial

Browser automation

OpenEAI has at least one signal for browser automation, but should be checked against a real task before adoption.

Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
Confirm official docs, current maintenance, license, and runtime constraints before production use.

partial

Coding agent workflow

OpenEAI has at least one signal for coding agent workflow, but should be checked against a real task before adoption.

Run a small repository change and inspect the diff, tests, and rollback path.
Confirm official docs, current maintenance, license, and runtime constraints before production use.

weak

Connector or protocol layer

OpenEAI is not primarily positioned for connector or protocol layer in the current metadata.

Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
Confirm official docs, current maintenance, license, and runtime constraints before production use.

weak

Evaluation and observability

OpenEAI is not primarily positioned for evaluation and observability in the current metadata.

Add one repeatable test case and confirm results can run again in review or CI.
Confirm official docs, current maintenance, license, and runtime constraints before production use.

Inputs and outputs

What an agent should inspect

Likely inputs

Repositories, files, issues, terminal output, and test results
Official setup instructions and a small real workflow

Likely outputs

Diffs, commits, explanations, test results, or review notes
A decision on whether this resource fits the target workflow

Evidence

Sources, claims, and missing checks

Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.

GitHub github

Repository source for code, license, issues, releases, and implementation details.

Homepage github

Repository source for code, license, issues, releases, and implementation details.

verified

OpenEAI is listed as open source.

License metadata: BSD-3-Clause

verified

OpenEAI has a recorded GitHub repository: eai-yeslab/OpenEAI-Arm.

Resource facts and GitHub source link.

inferred

OpenEAI supports these recorded deployment modes: self hosted, cloud.

OpenAgent decision signal metadata.

inferred

OpenEAI is tagged with robotics, messaging capabilities.

OpenAgent capability taxonomy.

Missing checks

Dedicated docs link is missing.
Repository freshness has not been recorded.

Next action

How to start evaluating OpenEAI

Inspect repository

Check license, recent activity, issues, examples, and security-sensitive code paths.

Open source

Inspect repository

Check license, recent activity, issues, examples, and security-sensitive code paths.

Open source

Install OpenEAI stack

Clone both repositories and follow the respective READMEs for hardware assembly and VLA training.

# Clone both repositories
git clone https://github.com/eai-yeslab/OpenEAI-Arm
git clone https://github.com/eai-yeslab/OpenEAI-VLA
# Follow the hardware assembly guide and training recipe in each repo

Compare

Alternatives and nearby resources

Use related resources to compare category fit, license, deployment model, and first-workflow behavior.

FAQ

Common questions about OpenEAI