> WrenAI is ***your AI data assistant*** that helps you get results and insights faster by asking questions without writing SQL.
## 🎯 Our Mission
WrenAI is dedicated to reimagining how businesses can interact with and leverage their data through LLM, by bringing comprehension capabilities to small and large data teams.
👉 [Learn more about our mission](https://docs.getwren.ai/overview/introduction)
## 👊 Why WrenAI?
### 1. Reduce Hallucination
> WrenAI offers detailed, explainable responses, ensuring users understand the origins and context of their data, thereby reducing ***hallucinations*** in LLMs.
### 2. Augment Your LLM Knowledge Base
> WrenAI enriches LLMs with your specific business context, with additional metadata for your data schema, such as semantics and relationships.
### 3. Self-Learning Feedback Loop
> WrenAI evolves with every interaction. It learns from user feedback and behavioral patterns, continuously refining its suggestions.
## 🤔 Benefits using WrenAI
WrenAI leverages Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) technology to enhance comprehension of internal data. Below are the three key benefits:
### 1. Fast Onboarding
> Discover and analyze your data with our user interface. Effortlessly generate results without needing to code.
### 2. Secure By Design
> Your database contents will never be transmitted to the LLM. Only metadata, like schemas, documentation, and queries, will be used in semantic search.
### 3. Open-Source
> Deploy WrenAI anywhere you like on your own data, LLM APIs, and environment, it's free.
## 🤖 WrenAI's Architecture
WrenAI is consist of three core services:
- ***[Wren UI](https://github.com/Canner/WrenAI/tree/main/wren-ui):*** An intuitive user interface for asking questions, defining data relationships, and integrating data sources within WrenAI's framework.
- ***[Wren AI Service](https://github.com/Canner/WrenAI/tree/main/wren-ai-service):*** Processes queries using a vector database for context retrieval, guiding LLMs to produce precise SQL outputs.
- ***[Wren Engine](https://github.com/Canner/wren-engine):*** Serves as the platform's backbone, managing metadata and connecting to data sources, while preparing for future application integrations.
## 🫣 Sneak Peek
| Data Modeling | Ask and Follow-up Questions |
| ---- | ---- |
|  |  |
## 🤞 Design Philosophies
We have some core design philosophies that were used when developing WrenAI.
- **Explainability**: WrenAI ensures that every SQL query generated in natural language is accurate, concise, and reliable.
- **Interoperability**: WrenAI enables users to query data from multiple sources without dealing with the complexities of different data formats and dialects, providing a standard interface across different sources.
- **Interactive Experience**: WrenAI is designed to engage users in a dialogue, clarifying their queries and refining results in real time.
- **Continuous Learning**: WrenAI will proactively learn through ongoing query history, feedback, and interactions. Incorporating new patterns, information, and data structures into our LLM knowledge base.
## 🚧 Project Status
WrenAI is currently in ***alpha version***. The project team is actively working on progress and aiming to release new versions at least biweekly.
## 🚀 Getting Started
Using WrenAI is super simple, you can setup within 3 minutes, and start to interact with your own data!
***Start Today And Be 100X More Productive Than Yesterday***
- Visit our [Installation Guide of WrenAI](http://docs.getwren.ai/installation).
- Visit the [Usage Guides](http://docs.getwren.ai/guide/connect/overview) to learn more about how to use WrenAI.
## 📚 Documentation
Visit [WrenAI documentation](https://docs.getwren.ai) to view the full documentation.
## ⭐️ Community
- Welcome to our [Discord server](https://discord.gg/5DvshJqG8Z) to give us feedback!
- If there is any issues, please visit [GitHub Issues](https://github.com/Canner/WrenAI/issues).
Do note that our [Code of Conduct](./CODE_OF_CONDUCT.md) applies to all WrenAI community channels. Users are **highly encouraged** to read and adhere to them to avoid repercussions.
