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Vanna AI

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Monthly visits
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23.3K
#51
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Vanna.AI is a personalized AI SQL agent that generates and runs accurate SQL for databases using LLMs via retrieval-augmented generation, with capabilities tied to the training data provided

FEATURES

  • 🤖 Personalized AI SQL Agent: Vanna helps generate and run accurate SQL for databases using LLMs via Retrieval-Augmented Generation. It is trained based on the provided data, with more training data leading to better accuracy for large and complex datasets.
  • ⚙️ Open-Source Integration: The Vanna Python package and various frontend integrations are open-source, allowing users to run Vanna on their own infrastructure and easily create connectors for different databases.
  • 🔒 Data Privacy: Vanna ensures data privacy by only interacting with the metadata storage layer, which only sees schemas, documentation, and queries. The actual database contents are never sent to the LLM.
  • 📈 Continuous Improvement: As Vanna is used, the model continuously improves by augmenting the training data, enhancing its accuracy and performance.
  • 💻 Versatile Deployment: Vanna can be started in a Jupyter Notebook and exposed to business users via Slackbot, web app, Streamlit app, or any other frontend, including integration into customer-facing web apps.

USE CASES

  • Quick, data-driven decisions: Vanna.AI allows you to ask data questions instantly, using AI-generated SQL for your database, enabling faster and more informed decision-making

ADDITIONAL INFO

Release
2023
Location
USA
Employees
1 - 10
Platforms
Laptop, Code
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FAQ

Vanna.ai offers several benefits, including:asier data retrieval for users without extensive SQL knowledge.educed risk of errors due to incomplete or incorrect definitions.mproved efficiency by leveraging AI and machine learning techniques
Vanna.ai connects and queries across disparate data sources, such as databases and event-based systems. It uses AI and machine learning to understand and process natural language queries, translating them into SQL queries and retrieving the desired data.

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