Best AI tools for< Define Data Models >

Amplication is an AI-powered platform for .NET and Node.js app development, offering the world's fastest way to build backend services. It empowers developers by providing customizable, production-ready backend services without vendor lock-ins. Users can define data models, extend and customize with plugins, generate boilerplate code, and modify the generated code freely. The platform supports role-based access control, microservices architecture, continuous Git sync, and automated deployment. Amplication is SOC-2 certified, ensuring data security and compliance.

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.

Dify is an open-source platform for building AI applications that combines Backend-as-a-Service and LLMOps to streamline the development of generative AI solutions. It integrates support for mainstream LLMs, an intuitive Prompt orchestration interface, high-quality RAG engines, a flexible AI Agent framework, and easy-to-use interfaces and APIs. Dify allows users to skip complexity and focus on creating innovative AI applications that solve real-world problems. It offers a comprehensive, production-ready solution with a user-friendly interface.

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.

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.

Caffe is a deep learning framework developed by Berkeley AI Research (BAIR) and community contributors. It is designed for speed, modularity, and expressiveness, allowing users to define models and optimization through configuration without hard-coding. Caffe supports both CPU and GPU training, making it suitable for research experiments and industry deployment. The framework is extensible, actively developed, and tracks the state-of-the-art in code and models. Caffe is widely used in academic research, startup prototypes, and large-scale industrial applications in vision, speech, and multimedia.

EyePop.ai is a hassle-free AI vision partner designed for innovators to easily create and own custom AI-powered vision models tailored to their visual data needs. The platform simplifies building AI-powered vision models through a fast, intuitive, and fully guided process without the need for coding or technical expertise. Users can define their target, upload data, train their model, deploy and detect, and iterate and improve to ensure effective AI solutions. EyePop.ai offers pre-trained model library, self-service training platform, and future-ready solutions to help users innovate faster, offer unique solutions, and make real-time decisions effortlessly.

Bot Resources is an AI application that helps companies define a vision for Generative AI, set up governance frameworks, design solutions for unique challenges, and automate business processes using agentic systems. The application offers tailored solutions, expertise in advanced language models, and strategic consulting for successful AI implementation.

Confident AI is an open-source evaluation infrastructure for Large Language Models (LLMs). It provides a centralized platform to judge LLM applications, ensuring substantial benefits and addressing any weaknesses in LLM implementation. With Confident AI, companies can define ground truths to ensure their LLM is behaving as expected, evaluate performance against expected outputs to pinpoint areas for iterations, and utilize advanced diff tracking to guide towards the optimal LLM stack. The platform offers comprehensive analytics to identify areas of focus and features such as A/B testing, evaluation, output classification, reporting dashboard, dataset generation, and detailed monitoring to help productionize LLMs with confidence.

Defined.ai is a leading provider of high-quality and ethical data for AI applications. Founded in 2015, Defined.ai has a global presence with offices in the US, Europe, and Asia. The company's mission is to make AI more accessible and ethical by providing a marketplace for buying and selling AI data, tools, and models. Defined.ai also offers professional services to help deliver success in complex machine learning projects.

Evoke AI is a cloud-based AI platform that provides a suite of tools for building and deploying AI models. The platform includes a drag-and-drop interface for creating models, a library of pre-trained models, and a set of tools for managing and deploying models. Evoke AI is designed to make AI accessible to businesses of all sizes, and it is used by a variety of organizations, including Fortune 500 companies and startups.

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.

ONNX is an open standard for machine learning interoperability, providing a common format to represent machine learning models. It defines a set of operators and a file format for AI developers to use models across various frameworks, tools, runtimes, and compilers. ONNX promotes interoperability, hardware access, and community engagement.

Windward is a Decision Support Platform that empowers organizations with actionable Maritime AI insights and Organization Defined Risk tailored to optimize operational readiness and supply chain risk management. It provides innovative AI models, daily vessel activities monitoring, and predictive risk insights for various industries such as trading, shipping, supply chain, logistics, government, and public sector. Windward offers a holistic view of maritime risk by fusing multiple data sources and applying advanced machine learning models. The platform helps in vessel screening, business growth, exception insights, and predictive risk insights.

Variational AI is a company that uses generative AI to discover novel drug-like small molecules with optimized properties for defined targets. Their platform, Enki™, is the first commercially accessible foundation model for small molecules. It is designed to make generating novel molecule structures easy, with no data required. Users simply define their target product profile (TPP) and Enki does the rest. Enki is an ensemble of generative algorithms trained on decades worth of experimental data with proven results. The company was founded in September 2019 and is based in Vancouver, BC, Canada.

Strat.Chat is an AI-based business strategy tool that assists business owners, potential founders, and entrepreneurs in evaluating business ideas, developing implementation plans, and providing comprehensive market data. Users can describe their business idea or existing model, and the tool uses artificial intelligence to analyze it in five steps: idea assessment, industry structure analysis, macroeconomic perspective, implementation plan, and market data. The tool offers customizable recommendations and the option for a 'Deep Dive' to delve into more detailed insights.

Sicara is a data and AI expert platform that helps clients define and implement data strategies, build data platforms, develop data science products, and automate production processes with computer vision. They offer services to improve data performance, accelerate data use cases, integrate generative AI, and support ESG transformation. Sicara collaborates with technology partners to provide tailor-made solutions for data and AI challenges. The platform also features a blog, job offers, and a team of experts dedicated to enhancing productivity and quality in data projects.

Snaplet is a data management tool for developers that provides AI-generated dummy data for local development, end-to-end testing, and debugging. It uses a real programming language (TypeScript) to define and edit data, ensuring type safety and auto-completion. Snaplet understands database structures and relationships, automatically transforming personally identifiable information and seeding data accordingly. It integrates seamlessly into development workflows, providing data where it's needed most: on local machines, for CI/CD testing, and preview environments.

Extracta.ai is an AI data extraction tool for documents and images that automates data extraction processes with easy integration. It allows users to define custom templates for extracting structured data without the need for training. The platform can extract data from various document types, including invoices, resumes, contracts, receipts, and more, providing accurate and efficient results. Extracta.ai ensures data security, encryption, and GDPR compliance, making it a reliable solution for businesses looking to streamline document processing.

OpenAiGeek is a comprehensive website dedicated to providing the latest updates on artificial intelligence (AI) news, tools, and chatbots. It serves as a valuable resource for individuals and businesses seeking to stay informed about the rapidly evolving field of AI. The website features a wide range of articles covering various AI-related topics, including news on the latest AI advancements, in-depth reviews of AI tools, and interviews with industry experts. OpenAiGeek also offers a directory of AI tools, making it easy for users to discover and explore different AI applications. Additionally, the website provides a platform for users to engage in discussions and share their experiences with AI.

Instructor for PHP is a library designed for structured data extraction in PHP, powered by Large Language Models (LLMs). It simplifies the process of extracting structured, validated data from unstructured text or chat sequences. Instructor enhances workflow by providing a response model, validation capabilities, and max retries for requests. It supports classes as response models and provides features like partial results, string input, extracting scalar and enum values, and specifying data models using PHP type hints or DocBlock comments. The library allows customization of validation and provides detailed event notifications during request processing. Instructor is compatible with PHP 8.2+ and leverages PHP reflection, Symfony components, and SaloonPHP for communication with LLM API providers.

Domino is an open source workflow management platform that provides an intuitive GUI for creating, editing, and monitoring workflows. It also offers a standard way of writing and publishing functional pieces that can be reused in multiple workflows. Domino is powered by Apache Airflow for top-tier workflows scheduling and monitoring.

Hof is a CLI tool that unifies data models, schemas, code generation, and a task engine. It allows users to augment data, config, and schemas with CUE to improve consistency, generate multiple Yaml and JSON files, explore data or config with a TUI, and run workflows with automatic task dependency inference. The tool uses CUE to power the DX and implementation, providing a language for specifying schemas, configuration, and writing declarative code. Hof offers core features like code generation, data model management, task engine, CUE cmds, creators, modules, TUI, and chat for better, scalable results.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

PyTorch Lightning is a framework for training and deploying AI models. It provides a high-level API that abstracts away the low-level details of PyTorch, making it easier to write and maintain complex models. Lightning also includes a number of features that make it easy to train and deploy models on multiple GPUs or TPUs, and to track and visualize training progress. PyTorch Lightning is used by a wide range of organizations, including Google, Facebook, and Microsoft. It is also used by researchers at top universities around the world. Here are some of the benefits of using PyTorch Lightning: * **Increased productivity:** Lightning's high-level API makes it easy to write and maintain complex models. This can save you time and effort, and allow you to focus on the research or business problem you're trying to solve. * **Improved performance:** Lightning's optimized training loops and data loading pipelines can help you train models faster and with better performance. * **Easier deployment:** Lightning makes it easy to deploy models to a variety of platforms, including the cloud, on-premises servers, and mobile devices. * **Better reproducibility:** Lightning's logging and visualization tools make it easy to track and reproduce training results.

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.

Wren Engine is a semantic engine designed to serve as the backbone of the semantic layer for LLMs. It simplifies the user experience by translating complex data structures into a business-friendly format, enabling end-users to interact with data using familiar terminology. The engine powers the semantic layer with advanced capabilities to define and manage modeling definitions, metadata, schema, data relationships, and logic behind calculations and aggregations through an analytics-as-code design approach. By leveraging Wren Engine, organizations can ensure a developer-friendly semantic layer that reflects nuanced data relationships and dynamics, facilitating more informed decision-making and strategic insights.

Neo4j Runway is a Python library that simplifies the process of migrating relational data into a graph. It provides tools to abstract communication with OpenAI for data discovery, generate data models, ingestion code, and load data into a Neo4j instance. The library leverages OpenAI LLMs for insights, Instructor Python library for modeling, and PyIngest for data loading. Users can visualize data models using graphviz and benefit from a seamless integration with Neo4j for efficient data migration.

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.

The NVIDIA AI Blueprint for Vulnerability Analysis for Container Security showcases accelerated analysis on common vulnerabilities and exposures (CVE) at an enterprise scale, reducing mitigation time from days to seconds. It enables security analysts to determine software package vulnerabilities using large language models (LLMs) and retrieval-augmented generation (RAG). The blueprint is designed for security analysts, IT engineers, and AI practitioners in cybersecurity. It requires NVAIE developer license and API keys for vulnerability databases, search engines, and LLM model services. Hardware requirements include L40 GPU for pipeline operation and optional LLM NIM and Embedding NIM. The workflow involves LLM pipeline for CVE impact analysis, utilizing LLM planner, agent, and summarization nodes. The blueprint uses NVIDIA NIM microservices and Morpheus Cybersecurity AI SDK for vulnerability analysis.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency. It helps users improve AI output quality through data quality, take control of their data and models, and improve efficiency by quickly iterating on the right data and models. Argilla is an open-source community-driven project that provides tools for achieving and maintaining high-quality data standards, with a focus on NLP and LLMs. It is used by AI teams from companies like the Red Cross, Loris.ai, and Prolific to improve the quality and efficiency of AI projects.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

HuggingFists is a low-code data flow tool that enables convenient use of LLM and HuggingFace models. It provides functionalities similar to Langchain, allowing users to design, debug, and manage data processing workflows, create and schedule workflow jobs, manage resources environment, and handle various data artifact resources. The tool also offers account management for users, allowing centralized management of data source accounts and API accounts. Users can access Hugging Face models through the Inference API or locally deployed models, as well as datasets on Hugging Face. HuggingFists supports breakpoint debugging, branch selection, function calls, workflow variables, and more to assist users in developing complex data processing workflows.

Ruby Nano Bots is an implementation of the Nano Bots specification supporting various AI providers like Cohere Command, Google Gemini, Maritaca AI MariTalk, Mistral AI, Ollama, OpenAI ChatGPT, and others. It allows calling tools (functions) and provides a helpful assistant for interacting with AI language models. The tool can be used both from the command line and as a library in Ruby projects, offering features like REPL, debugging, and encryption for data privacy.

Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.

r2ai is a tool designed to run a language model locally without internet access. It can be used to entertain users or assist in answering questions related to radare2 or reverse engineering. The tool allows users to prompt the language model, index large codebases, slurp file contents, embed the output of an r2 command, define different system-level assistant roles, set environment variables, and more. It is accessible as an r2lang-python plugin and can be scripted from various languages. Users can use different models, adjust query templates dynamically, load multiple models, and make them communicate with each other.

Define best social media platform for your marketing needs.

Define the right marketing metrics for your business

Put paper name or pdf to read. it will summarize wildly. If you want to get the meaning of glossary, write G.

Provides dry, accurate answers in a formal tone.

Numerologist creating grids and interpretations by user-defined rules.

Encrypts text based on pre-defined encryption table

I'll help you sense-check and define Behavioral Insights for your ideas!

Goal Planning Coach, here to help define and achieve your aspirations.

I create creative idea lists for products. Type /help to start. Example: define Product and Topic. Product: eCommerce Website Topic: New Features

Aide à la définitions des besoins des clients pour leur chantier de chape fluide.

Open Specification Schema for defining your GPT Assistant

A psychology dictionary for pros, quoting sources first, then summarizing in tables, with bilingual responses.

Your cheeky guide to fanfic lingo ✨📚

Personal Tutor for Specialized Academic Terms.

A GPT that provides detailed, dictionary-like explanations.

Legal terminology expert from Black's Law Dictionary, aiding in understanding sovereignty.

🌠 Adaptable, science explainer.

Defines and explains function calls based on a knowledge source.

Defines words and generates images, excluding specific narratives.

以易懂的示例、应用场景和最后的图像解释专有名词。