Best AI tools for< Create Test Datasets >

Syntho is a self-service AI-generated synthetic data platform that offers a comprehensive solution for generating synthetic data for various purposes. It provides tools for de-identification, test data management, rule-based synthetic data generation, data masking, and more. With a focus on privacy and accuracy, Syntho enables users to create synthetic data that mirrors real production data while ensuring compliance with regulations and data privacy standards. The platform offers a range of features and use cases tailored to different industries, including healthcare, finance, and public organizations.

Datagen is a platform that provides synthetic data for computer vision. Synthetic data is artificially generated data that can be used to train machine learning models. Datagen's data is generated using a variety of techniques, including 3D modeling, computer graphics, and machine learning. The company's data is used by a variety of industries, including automotive, security, smart office, fitness, cosmetics, and facial applications.

Bifrost AI is a data generation engine designed for AI and robotics applications. It enables users to train and validate AI models faster by generating physically accurate synthetic datasets in 3D simulations, eliminating the need for real-world data. The platform offers pixel-perfect labels, scenario metadata, and a simulated 3D world to enhance AI understanding. Bifrost AI empowers users to create new scenarios and datasets rapidly, stress test AI perception, and improve model performance. It is built for teams at every stage of AI development, offering features like automated labeling, class imbalance correction, and performance enhancement.

Future AGI is a revolutionary AI data management platform that aims to achieve 99% accuracy in AI applications across software and hardware. It provides a comprehensive evaluation and optimization platform for enterprises to enhance the performance of their AI models. Future AGI offers features such as creating trustworthy, accurate, and responsible AI, 10x faster processing, generating and managing diverse synthetic datasets, testing and analyzing agentic workflow configurations, assessing agent performance, enhancing LLM application performance, monitoring and protecting applications in production, and evaluating AI across different modalities.

Fine-Tune AI is a tool that allows users to generate fine-tune data sets using prompts. This can be useful for a variety of tasks, such as improving the accuracy of machine learning models or creating new training data for AI applications.

Webo.AI is a test automation platform powered by AI that offers a smarter and faster way to conduct testing. It provides generative AI for tailored test cases, AI-powered automation, predictive analysis, and patented AiHealing for test maintenance. Webo.AI aims to reduce test time, production defects, and QA costs while increasing release velocity and software quality. The platform is designed to cater to startups and offers comprehensive test coverage with human-readable AI-generated test cases.

testRigor is an AI-based test automation tool that allows users to create and execute test cases using plain English instructions. It leverages generative AI in software testing to automate test creation and maintenance, offering features such as no code/codeless testing, web, mobile, and desktop testing, Salesforce automation, and accessibility testing. With testRigor, users can achieve test coverage faster and with minimal maintenance, enabling organizations to reallocate QA engineers to build API tests and increase test coverage significantly. The tool is designed to simplify test automation, reduce QA headaches, and improve productivity by streamlining the testing process.

Katalon is a modern, comprehensive quality management platform that helps teams of any size deliver the highest quality digital experiences. It offers a range of features including test authoring, test management, test execution, reporting & analytics, and AI-powered testing. Katalon is suitable for testers of all backgrounds, providing a single platform for testing web, mobile, API, desktop, and packaged apps. With AI capabilities, Katalon simplifies test automation, streamlines testing operations, and scales testing programs for enterprise teams.

Rainforest QA is an AI-powered test automation platform designed for SaaS startups to streamline and accelerate their testing processes. It offers AI-accelerated testing, no-code test automation, and expert QA services to help teams achieve reliable test coverage and faster release cycles. Rainforest QA's platform integrates with popular tools, provides detailed insights for easy debugging, and ensures visual-first testing for a seamless user experience. With a focus on automating end-to-end tests, Rainforest QA aims to eliminate QA bottlenecks and help teams ship bug-free code with confidence.

Teste.ai is an AI-powered platform that allows users to create software testing scenarios and test cases using top-notch artificial intelligence technology. The platform offers a variety of tools based on AI to accelerate the software quality testing journey, helping testers cover a wide range of requirements with a vast array of test scenarios efficiently. Teste.ai's intelligent features enable users to save time and enhance efficiency in creating, executing, and managing software tests. With advanced AI integration, the platform provides automatic generation of test cases based on software documentation or specific requirements, ensuring comprehensive test coverage and precise responses to testing queries.

BlazeMeter by Perforce is an AI-powered continuous testing platform designed to automate testing processes and enhance software quality. It offers effortless test creation, seamless test execution, instant issue analysis, and self-sustaining maintenance. BlazeMeter provides a comprehensive solution for performance, functional, scriptless, API testing, and monitoring, along with test data and service virtualization. The platform enables teams to speed up digital transformation, shift quality left, and streamline DevOps practices. With AI analytics, scriptless test creation, and UX testing capabilities, BlazeMeter empowers users to drive innovation, accuracy, and speed in their test automation efforts.

The website offers an AI testing system that allows users to generate test questions instantly. It features a smart question bank, rapid question generation, and immediate test creation. Users can try out various test questions, such as generating knowledge test questions for car sales, company compliance standards, and real estate tax rate knowledge. The system ensures each test paper has similar content and difficulty levels. It also provides random question selection to reduce cheating possibilities. Employees can access the test link directly, view test scores immediately after submission, and check incorrect answers with explanations. The system supports single sign-on via WeChat for employee verification and record-keeping of employee rankings and test attempts. The platform prioritizes enterprise data security with a three-level network security rating, ISO/IEC 27001 information security management system, and ISO/IEC 27701 privacy information management system.

Softbuilder is a software development company that focuses on creating innovative database tools. Their products include ERBuilder Data Modeler, a database modeling software for high-quality data models, and AbstraLinx, a powerful metadata discovery tool for Salesforce. Softbuilder aims to provide straightforward tools that utilize the latest technology to help users be more productive and focus on delivering solutions rather than learning complicated tools.

SmartExam is an AI-powered platform designed to assist students in exam preparation by generating test exams based on uploaded lectures. The tool aims to help students succeed in their exams by providing tailored interactive exams and study materials. SmartExam is trusted by top students worldwide and offers a user-friendly experience. Users can upload lecture materials in PDF format, generate test exams in seconds, and download them for further training. The platform reduces exam preparation time by 50% and has received positive feedback for its efficiency and effectiveness.

QuarkIQL is a generative testing tool for computer vision APIs. It allows users to create custom test images and requests with just a few clicks. QuarkIQL also provides a log of your queries so you can run more experiments without starting from square one.

Eden AI is a full-stack AI platform designed for developers to efficiently create, test, and deploy AI solutions. It offers unified access to a wide range of AI models, a powerful workflow builder, and advanced monitoring tools. The platform enables users to integrate AI seamlessly into their projects, with features such as template-based workflow creation, AI model selection, cost monitoring, easy integration via API, and access to top AI technologies and cloud services.

Quizbot.ai is an advanced AI question generator designed to revolutionize the process of question and exam development. It offers a cutting-edge artificial intelligence system that can generate various types of questions from different sources like PDFs, Word documents, videos, images, and more. Quizbot.ai is a versatile tool that caters to multiple languages and question types, providing a personalized and engaging learning experience for users across various industries. The platform ensures scalability, flexibility, and personalized assessments, along with detailed analytics and insights to track learner performance. Quizbot.ai is secure, user-friendly, and offers a range of subscription plans to suit different needs.

Reflect is an AI-powered test automation tool that revolutionizes the way end-to-end tests are created, executed, and maintained. By leveraging Generative AI, Reflect eliminates the need for manual coding and provides a seamless testing experience. The tool offers features such as no-code test automation, visual testing, API testing, cross-browser testing, and more. Reflect aims to help companies increase software quality by accelerating testing processes and ensuring test adaptability over time.

Symflower is an AI-powered unit test generator for Java applications. It helps developers write and maintain test code with ease, saving time and improving code quality. Symflower works with JUnit 4 and JUnit 5 for Java, Spring, and Spring Boot applications.

The website 'Create Next App Chat With the Algorithm' is an AI tool that allows users to generate chat applications using algorithms. It is a work in progress with the latest algorithm code updated on April 14, 2023. Users can leverage this tool to quickly create chat applications with the help of advanced algorithms.

Ragas is a framework that helps you evaluate your Retrieval Augmented Generation (RAG) pipelines. RAG denotes a class of LLM applications that use external data to augment the LLM’s context. There are existing tools and frameworks that help you build these pipelines but evaluating it and quantifying your pipeline performance can be hard. This is where Ragas (RAG Assessment) comes in. Ragas provides you with the tools based on the latest research for evaluating LLM-generated text to give you insights about your RAG pipeline. Ragas can be integrated with your CI/CD to provide continuous checks to ensure performance.

Empirical is a tool that allows you to test different LLMs, prompts, and other model configurations across all the scenarios that matter for your application. With Empirical, you can run your test datasets locally against off-the-shelf models, test your own custom models and RAG applications, view, compare, and analyze outputs on a web UI, score your outputs with scoring functions, and run tests on CI/CD.

Eval-Scope is a framework for evaluating and improving large language models (LLMs). It provides a set of commonly used test datasets, metrics, and a unified model interface for generating and evaluating LLM responses. Eval-Scope also includes an automatic evaluator that can score objective questions and use expert models to evaluate complex tasks. Additionally, it offers a visual report generator, an arena mode for comparing multiple models, and a variety of other features to support LLM evaluation and development.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

A public repository collecting links to state-of-the-art training sets, QA, benchmarks and other evaluations for various ML and LLM applications in materials science and chemistry. It includes datasets related to chemistry, materials, multimodal data, and knowledge graphs in the field. The repository aims to provide resources for training and evaluating machine learning models in the materials science and chemistry domains.

Odyssey is a framework designed to empower agents with open-world skills in Minecraft. It provides an interactive agent with a skill library, a fine-tuned LLaMA-3 model, and an open-world benchmark for evaluating agent capabilities. The framework enables agents to explore diverse gameplay opportunities in the vast Minecraft world by offering primitive and compositional skills, extensive training data, and various long-term planning tasks. Odyssey aims to advance research on autonomous agent solutions by providing datasets, model weights, and code for public use.

OmAgent is an open-source agent framework designed to streamline the development of on-device multimodal agents. It enables agents to empower various hardware devices, integrates speed-optimized SOTA multimodal models, provides SOTA multimodal agent algorithms, and focuses on optimizing the end-to-end computing pipeline for real-time user interaction experience. Key features include easy connection to diverse devices, scalability, flexibility, and workflow orchestration. The architecture emphasizes graph-based workflow orchestration, native multimodality, and device-centricity, allowing developers to create bespoke intelligent agent programs.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

ZipPy is a research repository focused on fast AI detection using compression techniques. It aims to provide a faster approximation for AI detection that is embeddable and scalable. The tool uses LZMA and zlib compression ratios to indirectly measure the perplexity of a text, allowing for the detection of low-perplexity text. By seeding a compression stream with AI-generated text and comparing the compression ratio of the seed data with the sample appended, ZipPy can identify similarities in word choice and structure to classify text as AI or human-generated.

Apollo is a multilingual medical LLM that covers English, Chinese, French, Hindi, Spanish, Hindi, and Arabic. It is designed to democratize medical AI to 6B people. Apollo has achieved state-of-the-art results on a variety of medical NLP tasks, including question answering, medical dialogue generation, and medical text classification. Apollo is easy to use and can be integrated into a variety of applications, making it a valuable tool for healthcare professionals and researchers.

`npcsh` is a python-based command-line tool designed to integrate Large Language Models (LLMs) and Agents into one's daily workflow by making them available and easily configurable through the command line shell. It leverages the power of LLMs to understand natural language commands and questions, execute tasks, answer queries, and provide relevant information from local files and the web. Users can also build their own tools and call them like macros from the shell. `npcsh` allows users to take advantage of agents (i.e. NPCs) through a managed system, tailoring NPCs to specific tasks and workflows. The tool is extensible with Python, providing useful functions for interacting with LLMs, including explicit coverage for popular providers like ollama, anthropic, openai, gemini, deepseek, and openai-like providers. Users can set up a flask server to expose their NPC team for use as a backend service, run SQL models defined in their project, execute assembly lines, and verify the integrity of their NPC team's interrelations. Users can execute bash commands directly, use favorite command-line tools like VIM, Emacs, ipython, sqlite3, git, pipe the output of these commands to LLMs, or pass LLM results to bash commands.

LLM-Merging is a repository containing starter code for the LLM-Merging competition. It provides a platform for efficiently building LLMs through merging methods. Users can develop new merging methods by creating new files in the specified directory and extending existing classes. The repository includes instructions for setting up the environment, developing new merging methods, testing the methods on specific datasets, and submitting solutions for evaluation. It aims to facilitate the development and evaluation of merging methods for LLMs.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.

Ianvs is a distributed synergy AI benchmarking project incubated in KubeEdge SIG AI. It aims to test the performance of distributed synergy AI solutions following recognized standards, providing end-to-end benchmark toolkits, test environment management tools, test case control tools, and benchmark presentation tools. It also collaborates with other organizations to establish comprehensive benchmarks and related applications. The architecture includes critical components like Test Environment Manager, Test Case Controller, Generation Assistant, Simulation Controller, and Story Manager. Ianvs documentation covers quick start, guides, dataset descriptions, algorithms, user interfaces, stories, and roadmap.

I create Playwright test cases for specific URLs.

Creates Application Security Test cases in YAML

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Crafting full, accurate Apex test classes, with 100% user service.

Ensures software quality through automated testing strategies.

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Expert at crafting engaging questions like Rob Fitzpatrick

Assists teachers in marking tests and generating score reports.

Generates cybersecurity audit and penetration test specifications.

AI Voice Generation Expert - FREE TEST

Test your wit with RiddleGPT's playful puzzles!

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I am not affiliated with Bullhorn, nor do I have rights to this software. For this, please visit Bullhorn.com as they are the owner. The rights holders may ask me to remove this test bot.

Put your prompt engineering skills to the ultimate test! Embark on a journey to outwit a mythical guardian of ancient secrets. Try to extract the secret passphrase hidden in the system prompt and enter it in chat when you think you have it and claim your glory. Good luck!

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