Best AI tools for< Generate Queries >

Mikie.AI is an AI-powered tool that allows users to generate SQL queries in seconds using natural language. It simplifies the process of creating efficient SQL queries by leveraging AI technology. Users can define database schemas easily, translate SQL to English, and benefit from simple pricing plans. Mikie.AI aims to make SQL query generation error-free and accessible to all types of users, even those with limited SQL knowledge.

DB Sensei is an AI-powered SQL tool that helps developers generate, fix, explain, and format SQL queries with ease. It features a user-friendly interface, AI-driven query generation, query fixing, query explaining, and query formatting. DB Sensei is designed for developers, database administrators, and students who want to get faster results and improve their database skills.

SQLyze is an AI SQL generator that revolutionizes the way users interact with SQL queries. By leveraging artificial intelligence, SQLyze simplifies the process of crafting complex SQL queries into a user-friendly three-step approach. Users can effortlessly describe their data needs, add database schema details, and receive custom AI-generated SQL queries tailored to their specific requirements. With SQLyze, users can streamline their SQL querying process and enhance query accuracy, ultimately saving time and improving productivity.

Avanty is an AI assistant designed for data analysts using Metabase. It is an AI-powered Chrome extension that supports data analysts in their work by saving time on generating, editing, and understanding SQL queries. Avanty helps users in writing, editing, and debugging SQL queries, providing smart explanations and formatting to make the process easier and faster. It offers features like auto-generating SQL queries from natural language, auto-formatting queries, auto-suggestions for chart titles, and smart error debugging. Avanty aims to enhance the workflow of data analysts by simplifying SQL query tasks and providing intelligent assistance.

Vanna.AI is a personalized AI SQL agent that allows users to get actionable insights from their database by simply asking questions. It helps users to write SQL queries efficiently and quickly, even if they are not SQL experts. The application is open-source, highly accurate on complex datasets, secure, self-learning, and supports various databases. Vanna.AI is fully customizable to match unique needs and offers different front-end integrations for user convenience.

Text2SQL.AI is an AI-powered SQL query builder that helps users generate optimized SQL queries effortlessly. It supports various AI-powered services, including SQL query building from textual instructions, SQL query explanation to plain English, SQL query error fixation, adding custom database schemas, SQL dialects for various database types, Microsoft Excel and Google Sheets formula generation and explanation, and Regex expression generation and explanation. The tool is designed to improve SQL skills, save time, and assist beginners, data analysts, data scientists, data engineers, and software developers in their work.

AI Query is a powerful tool that allows users to generate SQL queries in seconds using simple English. With AI Query, anyone can create efficient SQL queries, without even knowing a thing about it. AI Query is easy to use and affordable, making it a great choice for businesses of all sizes.

SQL Builder is an AI-powered SQL query generator that allows users to easily generate complex SQL queries without writing any code. It offers a range of features such as a no-code SQL builder, SQL syntax explainer, SQL optimizer, SQL formatter, NoSQL query builder, and SQL syntax validator. SQL Builder supports various databases including MySQL, MariaDB, SQLite, PostgreSQL, Oracle, Microsoft SQL Server, MongoDB, BigQuery, Snowflake, and Amazon Redshift.

SQLAI.ai is a professional SQL multi-tool that leverages AI technology to generate, fix, explain, and optimize SQL queries and databases. It enables users to interact with SQL using everyday language, effortlessly train AI to understand database schemas, and benefit from AI-driven recommendations for query optimization. The platform caters to a wide range of users, from beginners to experts, by simplifying SQL tasks and providing valuable insights for database management. With features like generating SQL data, data analytics, and real-time data insights, SQLAI.ai revolutionizes the way users interact with databases, making SQL tasks simpler, more efficient, and accessible to all.

SQLPilot is an AI-first SQL editor that leverages artificial intelligence to help users quickly generate complex SQL queries. The tool supports multiple GPT models, offers SQL autocomplete, ensures privacy and security by not storing user data, and allows users to download query results in CSV format. With SQLPilot, users can write prompts in natural language, mention required tables, and let the AI model generate the query with all the necessary context. Testimonials from users highlight the tool's efficiency, accuracy, and time-saving capabilities in database management.

SQL Genius is an AI-powered tool that helps you translate English language queries into SQL queries. It is designed to make it easier for non-technical users to access and use SQL databases. With SQL Genius, you can simply type in your question in plain English, and the tool will automatically generate the corresponding SQL query. This can save you a lot of time and effort, and it can also help you to avoid errors.

Sequel is an AI-powered tool that serves as a natural language interface for databases, allowing users to effortlessly navigate and understand their data without the need to write complex SQL queries. By simply asking questions in plain English, users can quickly obtain insights and visualizations from their database. The tool supports a wide range of databases and services, ensuring users can connect to their existing database securely and efficiently. Sequel's AI capabilities enable users to generate SQL queries, uncover insights, and make better decisions based on the data analysis.

Fluent is an AI-powered data analytics platform that helps businesses explore their data and uncover insights. It uses natural language processing to understand user questions and generate SQL queries to retrieve data from a variety of sources. Fluent also provides visualizations and dashboards to help users understand their data and make informed decisions.

Outerbase is an AI-powered database platform that allows users to view, query, visualize, and edit their data. It features an AI Copilot, EZQL™, that can answer questions and generate SQL queries, a table editor that makes it easy to work with data, and a variety of plugins and themes to customize the experience. Outerbase integrates with most popular databases, including Postgres, MySQL, BigQuery, and Snowflake.

CensysGPT Beta is a tool that simplifies building queries and empowers users to conduct efficient and effective reconnaissance operations. It enables users to quickly and easily gain insights into hosts on the internet, streamlining the process and allowing for more proactive threat hunting and exposure management.

Blaze SQL AI is an AI Data Analytics chatbot and SQL generator that helps non-technical users and teams turn questions into data insights. It allows users to make their teams more informed and save time by using AI for Data Analysis on their SQL Database. Blaze SQL AI can write SQL code, run queries, visualize data, and provide database documentation. It is trusted by innovative teams and offers a private desktop version for secure data connections. The tool is designed to help users easily interact with their databases using natural language and generate complex SQL queries with the help of AI technology.

FormulaGenerator is a free AI-powered toolkit that helps users generate Excel formulas, VBA automations, and SQL queries. It also offers features like error spotting, formula explanations, code generation, and an AnswerBot powered by ChatGPT. The tool is available as a web app and a Google Sheets extension.

GPT Excel is an AI-powered tool that helps users generate spreadsheet formulas, SQL queries, Apps Script and VBA scripts easily. It supports over 50 languages and offers a free tier with limited requests per day. The pro plan includes additional features such as unlimited requests, priority customer support, and access to additional AI tools like a regex generator and an Excel template generator.

NLSQL is a B2B SaaS tool that empowers employees with an intuitive text interface to inform and speed up business decisions with significant benefits for enterprises. It works as the first NLP to SQL API, which doesn't require any sensitive or confidential data transfer outside the corporate IT ecosystem. NLSQL supports integrations to all main database types and corporate messengers, which helps drive businesses forward faster with data-driven business decisions.

vizGPT is an AI-powered data visualization tool that simplifies the process of turning complex data into clear insights. The software offers contextual understanding, intelligent conversation, and natural language processing capabilities to help users quickly generate and understand complex visualizations. With real-time responses and contextual memory features, vizGPT provides a seamless data storytelling experience. Users can create visualizations using a no-code GUI with drag-and-drop functionality and leverage powerful data transformation and profiling tools. vizGPT aims to revolutionize data visualization by offering an intuitive and efficient solution for data analysis.

PremSQL is an open-source library designed to help developers create secure, fully local Text-to-SQL solutions using small language models. It provides essential tools for building and deploying end-to-end Text-to-SQL pipelines with customizable components, ideal for secure, autonomous AI-powered data analysis. The library offers features like Local-First approach, Customizable Datasets, Robust Executors and Evaluators, Advanced Generators, Error Handling and Self-Correction, Fine-Tuning Support, and End-to-End Pipelines. Users can fine-tune models, generate SQL queries from natural language inputs, handle errors, and evaluate model performance against predefined metrics. PremSQL is extendible for customization and private data usage.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

WrenAI is a data assistant tool that helps users get results and insights faster by asking questions in natural language, without writing SQL. It leverages Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) technology to enhance comprehension of internal data. Key benefits include fast onboarding, secure design, and open-source availability. WrenAI consists of three core services: Wren UI (intuitive user interface), Wren AI Service (processes queries using a vector database), and Wren Engine (platform backbone). It is currently in alpha version, with new releases planned biweekly.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

TigerGraph CoPilot is an AI assistant that combines graph databases and generative AI to enhance productivity across various business functions. It includes three core component services: InquiryAI for natural language assistance, SupportAI for knowledge Q&A, and QueryAI for GSQL code generation. Users can interact with CoPilot through a chat interface on TigerGraph Cloud and APIs. CoPilot requires LLM services for beta but will support TigerGraph's LLM in future releases. It aims to improve contextual relevance and accuracy of answers to natural-language questions by building knowledge graphs and using RAG. CoPilot is extensible and can be configured with different LLM providers, graph schemas, and LangChain tools.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

VMind is an open-source solution for intelligent visualization, providing an intelligent chart component based on LLM by VisActor. It allows users to create chart narrative works with natural language interaction, edit charts through dialogue, and export narratives as videos or GIFs. The tool is easy to use, scalable, supports various chart types, and offers one-click export functionality. Users can customize chart styles, specify themes, and aggregate data using LLM models. VMind aims to enhance efficiency in creating data visualization works through dialogue-based editing and natural language interaction.

Vanna is an open-source Python framework for SQL generation and related functionality. It uses Retrieval-Augmented Generation (RAG) to train a model on your data, which can then be used to ask questions and get back SQL queries. Vanna is designed to be portable across different LLMs and vector databases, and it supports any SQL database. It is also secure and private, as your database contents are never sent to the LLM or the vector database.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

Awesome Text2SQL is a curated repository containing tutorials and resources for Large Language Models, Text2SQL, Text2DSL, Text2API, Text2Vis, and more. It provides guidelines on converting natural language questions into structured SQL queries, with a focus on NL2SQL. The repository includes information on various models, datasets, evaluation metrics, fine-tuning methods, libraries, and practice projects related to Text2SQL. It serves as a comprehensive resource for individuals interested in working with Text2SQL and related technologies.

Dataherald is a natural language-to-SQL engine built for enterprise-level question answering over structured data. It allows you to set up an API from your database that can answer questions in plain English. You can use Dataherald to: * Allow business users to get insights from the data warehouse without going through a data analyst * Enable Q+A from your production DBs inside your SaaS application * Create a ChatGPT plug-in from your proprietary data

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

QMedia is an open-source multimedia AI content search engine designed specifically for content creators. It provides rich information extraction methods for text, image, and short video content. The tool integrates unstructured text, image, and short video information to build a multimodal RAG content Q&A system. Users can efficiently search for image/text and short video materials, analyze content, provide content sources, and generate customized search results based on user interests and needs. QMedia supports local deployment for offline content search and Q&A for private data. The tool offers features like content cards display, multimodal content RAG search, and pure local multimodal models deployment. Users can deploy different types of models locally, manage language models, feature embedding models, image models, and video models. QMedia aims to spark new ideas for content creation and share AI content creation concepts in an open-source manner.

Awesome Generative AI & LLM APIs is a curated list of useful APIs that allow developers to integrate generative models into their applications without building the models from scratch. These APIs provide an interface for generating text, images, or other content, and include pre-trained language models for various tasks. The goal of this project is to create a hub for developers to create innovative applications, enhance user experiences, and drive progress in the AI field.

RAGoon is a high-level library designed for batched embeddings generation, fast web-based RAG (Retrieval-Augmented Generation) processing, and quantized indexes processing. It provides NLP utilities for multi-model embedding production, high-dimensional vector visualization, and enhancing language model performance through search-based querying, web scraping, and data augmentation techniques.

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