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claude-skill

Orbit: Host AI Privately

Get private RAG and multi-model apps with Orbit, a self-hosted AI infrastructure for founders, with 276 GitHub stars.
advanced⏱ 1-2 hoursπŸ’΅ Free (self-hosted)
321 stars56 forksPythonQuality 9/10Updated 7/26/2026100% free Β· open source
What it is

Host your own AI infrastructure privately with Orbit, allowing you to control and manage your AI applications securely.

What you can make with it

Private RAG and multi-model applications, such as a custom chatbot that provides personalized product recommendations to customers.

How it helps

Using Orbit helps you maintain data privacy and security, which is essential for businesses and individuals who handle sensitive information, by giving you full control over your AI infrastructure.

Real use case example

"A founder of an e-commerce startup wants to create a personalized product recommendation system for their customers. They use Orbit to host their AI infrastructure privately, then integrate it with their product database and website. As a result, they can provide customized product suggestions to their customers while keeping their data secure."

If you're new

A beginner should pick up Orbit when they need to create a private AI application and want to maintain control over their data and infrastructure.

If you're senior

A senior engineer or founder would reach for Orbit when they require a self-hosted, customizable AI infrastructure solution that prioritizes data privacy and security.

Common confusion cleared up

Orbit is often confused with cloud-based AI services, but it is specifically designed for self-hosted, private AI infrastructure, giving users full control over their data and applications.

Pairs with
ElasticsearchClaude APINotion database
Why we list it on WorkflowStacks: This skill is included in the marketplace because it offers a self-hosted, open-source solution for private AI infrastructure, providing an alternative to paid services.
What it does

Provides a complete, self-hosted AI infrastructure that lets startups build private AI applications with full data control and flexible model integration.

When to use it
  • β€’When you need a custom AI solution with sensitive data that can't be sent to external APIs
  • β€’For startups building enterprise AI tools requiring strict data privacy
  • β€’When you want to easily switch between different AI models without vendor lock-in
Quick start
  1. 1Clone the GitHub repository
  2. 2Configure your desired AI models and data sources in the configuration files
  3. 3Set up your local or cloud deployment environment
  4. 4Launch the Orbit infrastructure and start building your AI application
Ready-to-paste prompt
python orbit.py --deploy-mode local --model mistral --datasource ./company_documents
Saves to your device

Topics

ai-assistant
ai-gateway
ai-safety
anthropic
chatbot
developer-tools
elasticsearch
llm
mongodb
natural-language-to-sql
ollama-client
openai
python
rag
retrieval-augmented-generation
self-hosted
speech-to-text
text-to-speech
vector-database
What's inside β€” free to inspect
No purchase needed

Read the entire source before you build β€” unlike paid marketplaces that hide it behind a buy button.

12
top-level files
9
folders
113.2M
repo size
Apache-2.0
license
Key files
README.md
File tree
bin/
clients/
config/
docker/
docs/
examples/
install/
server/
utils/
.gitattributes
.gitignore
CHANGELOG.md
CLAUDE.md
CODE_OF_CONDUCT.md
conformance-baseline.yml
CONTRIBUTING.md
env.example
LICENSE
README.md
ruff.toml
SECURITY.md
Quick Actions
Details
Creator
schmitech
Language
Python
Category
claude-skill
Published
3/10/2025

Are you the creator of this tool? Claim your listing β†’ and earn 85% of every sale.

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