Vanna AI: Your Python-based AI SQL Co-pilot

Overview:

          Vanna AI is a revolutionary tool designed to streamline the process of writing complex SQL. It serves as a co-pilot for data-savvy individuals such as data analysts, data scientists, and engineers, helping them automate SQL writing.

Users:

          The initial users of Vanna AI are data-savvy data analysts, data scientists, engineers, and similar people that use Vanna to automate writing complex SQL.

Goal:

          The primary goal of Vanna AI is to help data people that know Python write SQL faster using AI.

Uses and Features:

          1. Training Data Management: Vanna AI allows users to train a model specific to their database for more accurate and tailored answers.

          2. Flagging Queries for Review: It provides the ability to flag queries for review, ensuring the accuracy of the generated SQL.

          3. Self-Correcting: Vanna AI is capable of self-correcting, improving its performance over time.

          4. Analyst Supervision: It offers analyst supervision, allowing for human oversight of the AI's operations.

          5. Transparent Accuracy: Vanna AI is transparent about its accuracy, providing users with confidence in the SQL it generates.

How it Works:

          1. Vanna AI uses a form of generative AI called Large Language Models (LLMs) which are trained on huge corpuses of data.

          2. It predicts the most likely next word or "token" in a response to a prompt.

          3. Vanna AI optimizes both the prompt and fine-tunes the LLM model to generate better SQL.

          4. It uses different LLMs to get the most accurate results.

          5. Over time, Vanna AI continues to improve its understanding of your schema and gets more and more questions right.

Customer Companies Statistics:

          1. Trusted Users: It is trusted by data-savvy data analysts, data scientists, engineers, and similar people.

          2. Rating: It has received 2.1k stars on GitHub.

          3. Work Done: It has helped users automate the writing of complex SQL.

          4. Products: It offers a Python package that can be used in various delivery mechanisms.

          5. Market Presence: It has a significant presence in the market, with its open-source version available for use.

          6. Tools: It is a set of tools that help you generate SQL using LLMs.