Best AI tools for< Model Data In A Sql Database >

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.

Deepnote is an AI-powered analytics and data science notebook platform designed for teams. It allows users to turn notebooks into powerful data apps and dashboards, combining Python, SQL, R, or even working without writing code at all. With Deepnote, users can query various data sources, generate code, explain code, and create interactive visualizations effortlessly. The platform offers features like collaborative workspaces, scheduling notebooks, deploying APIs, and integrating with popular data warehouses and databases. Deepnote prioritizes security and compliance, providing users with control over data access and encryption. It is loved by a community of data professionals and widely used in universities and by data analysts and scientists.

Fleak AI Workflows is a low-code serverless API Builder designed for data teams to effortlessly integrate, consolidate, and scale their data workflows. It simplifies the process of creating, connecting, and deploying workflows in minutes, offering intuitive tools to handle data transformations and integrate AI models seamlessly. Fleak enables users to publish, manage, and monitor APIs effortlessly, without the need for infrastructure requirements. It supports various data types like JSON, SQL, CSV, and Plain Text, and allows integration with large language models, databases, and modern storage technologies.

Dflux is a cloud-based Unified Data Science Platform that offers end-to-end data engineering and intelligence with a no-code ML approach. It enables users to integrate data, perform data engineering, create customized models, analyze interactive dashboards, and make data-driven decisions for customer retention and business growth. Dflux bridges the gap between data strategy and data science, providing powerful SQL editor, intuitive dashboards, AI-powered text to SQL query builder, and AutoML capabilities. It accelerates insights with data science, enhances operational agility, and ensures a well-defined, automated data science life cycle. The platform caters to Data Engineers, Data Scientists, Data Analysts, and Decision Makers, offering all-round data preparation, AutoML models, and built-in data visualizations. Dflux is a secure, reliable, and comprehensive data platform that automates analytics, machine learning, and data processes, making data to insights easy and accessible for enterprises.

Accio is a data modeling tool that allows users to define consistent relationships, metrics, and expressions for on-the-fly computations in reports and dashboards across various BI tools. It provides a syntax similar to GraphQL that allows users to define models, relationships, and metrics in a human-readable format. Accio also offers a user-friendly interface that provides data analysts with a holistic view of the relationships between their data models, enabling them to grasp the interconnectedness and dependencies within their data ecosystem. Additionally, Accio utilizes DuckDB as a caching layer to accelerate query performance for BI tools.

Athena Intelligence is an AI-native analytics platform and artificial employee designed to accelerate analytics workflows by offering enterprise teams co-pilot and auto-pilot modes. Athena learns your workflow as a co-pilot, allowing you to hand over controls to her for autonomous execution with confidence. With Athena, everyone in your enterprise has access to a data analyst, and she doesn't take days off. Simple integration to your Enterprise Data Warehouse Chat with Athena to query data, generate visualizations, analyze enterprise data and codify workflows. Athena's AI learns from existing documentation, data and analyses, allowing teams to focus on creating new insights. Athena as a platform can be used collaboratively with co-workers or Athena, with over 100 users in the same report or whiteboard environment concurrently making edits. From simple queries and visualizations to complex industry specific workflows, Athena enables you with SQL and Python-based execution environments.

Tactic is an AI-powered platform that provides generative insights and solutions for customers by leveraging AI technology to generate target accounts unique to businesses and new customer insights from various data sources. It offers features such as no-code custom AI builder, process automation, multi-step reasoning, model agnostic data import, and simple user experience. Tactic is trusted by hypergrowth startups and Fortune 500 companies for market research, audience automation, and customer data management. The platform helps users increase revenue, save time on research and analysis, and close more deals efficiently.

Dobb·E is an open-source, general framework for learning household robotic manipulation. It aims to create a 'generalist machine' for homes that can adapt and learn various tasks cost-effectively. Dobb·E can learn a new task in just five minutes of demonstration, thanks to a tool called 'The Stick' for data collection. The system achieved an 81% success rate in completing 109 tasks across 10 homes in New York City. Dobb·E is designed to accelerate research on home robots and make robot assistants a common sight in households.

xAI Grok is a visual analytics platform that helps users understand and interpret machine learning models. It provides a variety of tools for visualizing and exploring model data, including interactive charts, graphs, and tables. xAI Grok also includes a library of pre-built visualizations that can be used to quickly get started with model analysis.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Neptune is an MLOps stack component for experiment tracking. It allows users to track, compare, and share their models in one place. Neptune is used by scaling ML teams to skip days of debugging disorganized models, avoid long and messy model handovers, and start logging for free.

GPT-4o is a state-of-the-art AI model developed by OpenAI, capable of processing and generating text, audio, and image outputs. It offers enhanced emotion recognition, real-time interaction, multimodal capabilities, improved accessibility, and advanced language capabilities. GPT-4o provides cost-effective and efficient AI solutions with superior vision and audio understanding. It aims to revolutionize human-computer interaction and empower users worldwide with cutting-edge AI technology.

Jynnt is an AI application designed to simplify and enhance the user's AI experience. It offers a wide range of AI models, folders, and tags in a light, organized, and efficient workspace. With over 100 stellar AI models, users have limitless choices and can enjoy clutter-free organization with folders and tags. The application features a lightweight interface, unlimited exploration without restrictions, and a super efficient workspace for innovation. Jynnt also provides 24/7 support to assist users in their AI journey.

The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.

HostAI is a platform that allows users to host their artificial intelligence models and applications with ease. It provides a user-friendly interface for managing and deploying AI projects, eliminating the need for complex server setups. With HostAI, users can seamlessly run their AI algorithms and applications in a secure and efficient environment. The platform supports various AI frameworks and libraries, making it versatile for different AI projects. HostAI simplifies the process of AI deployment, enabling users to focus on developing and improving their AI models.

LLMChess is a web-based chess game that utilizes large language models (LLMs) to power the gameplay. Players can select the LLM model they wish to play against, and the game will commence once the "Start" button is clicked. The game logs are displayed in a black-bordered pane on the right-hand side of the screen. LLMChess is compatible with the Google Chrome browser. For more information on the game's functionality and participation guidelines, please refer to the provided link.

MeetYou is an AI application that allows users to create and interact with their own digital entity, preserving their experiences, memories, and thoughts in a structured manner. Users can personalize their entity, engage in interactions through chat, voice, or video, and even monetize these interactions. The application leverages over 150 data sources to enrich the user's entity and offers features like 3D cloning, memory effect for evolution, and modular configurability. MeetYou aims to help users build a digital legacy and connect with others through collective intelligence.

Surge AI is a data labeling platform that provides human-generated data for training and evaluating large language models (LLMs). It offers a global workforce of annotators who can label data in over 40 languages. Surge AI's platform is designed to be easy to use and integrates with popular machine learning tools and frameworks. The company's customers include leading AI companies, research labs, and startups.

Genailia is an AI platform that offers a range of products and services such as translation, transcription, chatbot, LLM, GPT, TTS, ASR, and social media insights. It harnesses AI to redefine possibilities by providing generative AI, linguistic interfaces, accelerators, and more in a single platform. The platform aims to streamline various tasks through AI technology, making it a valuable tool for businesses and individuals seeking efficient solutions.

Novita AI is an AI cloud platform offering Model APIs, Serverless, and GPU Instance services in a cost-effective and integrated manner to accelerate AI businesses. It provides optimized models for high-quality dialogue use cases, full spectrum AI APIs for image, video, audio, and LLM applications, serverless auto-scaling based on demand, and customizable GPU solutions for complex AI tasks. The platform also includes a Startup Program, 24/7 service support, and has received positive feedback for its reasonable pricing and stable services.

This repository contains samples to help design AI applications using data from an Azure SQL Database. It showcases technical concepts and workflows integrating Azure SQL data with popular AI components both within and outside Azure. The samples cover various AI features such as Azure Cognitive Services, Promptflow, OpenAI, Vanna.AI, Content Moderation, LangChain, and more. Additionally, there are end-to-end samples like Similar Content Finder, Session Conference Assistant, Chatbots, Vectorization, SQL Server Database Development, Redis Vector Search, and Similarity Search with FAISS.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.

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.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Expert in SQL queries, and Tutoring.

Takes in a Project Design Document and generates a database schema diagram for the project.

Expert in generating and debugging Neo4j code, with explanations on graph database principles.

The IlluminatiAI model represents a novel approach in the field of artificial intelligence, incorporating elements of secret societies, ancient knowledge, and hidden wisdom into its algorithms.

The Turing Test, first named the imitation game by Alan Turing in 1950, is a measure of a machine's capacity to demonstrate intelligence that's either equal to or indistinguishable from human intelligence.

Expert in synthetic neurobiology, brain organoids, and AI applications in neuroscience. Powered by Breebs (www.breebs.com)

Guides in data engineering tasks with a focus on practical solutions.

A dual-expert in Pydantic V1 and V2, adept at online research for V2.

A creative aide for designing new GPT models, skilled in ideation and prompting.

I am a digital scientist skilled in Python, here to assist with scientific and data analysis tasks.

Economist panel of Smith, Marx, Schumpeter, Hayek, Friedman, and Keynes in debate.

Expert in data disclosure risk analysis, mitigation, and modeling methods.

Your friend and helper in the database world!

Expert in Marian NMT models and training

Expert in ML model optimization and tuning!

Assists with ROMS and COAWST modeling in Linux environments.

Apply gold-standard startup valuation and assessment methods to identify risks and gaps in your business model and product ideas.

Bot that guides users in understanding the Cognitive-Theoretic Model of the Universe

Expert in refining custom GPT model instructions.

AI language model specializing in orchestrating human-AI interactions