Best AI tools for< Performance Testing >

Tricentis is an AI-powered testing tool that offers a comprehensive set of test automation capabilities to address various testing challenges. It provides end-to-end test automation solutions for a wide range of applications, including Salesforce, mobile testing, performance testing, and data integrity testing. Tricentis leverages advanced ML technologies to enable faster and smarter testing, ensuring quality at speed with reduced risk, time, and costs. The platform also offers continuous performance testing, change and data intelligence, and model-based, codeless test automation for mobile applications.

bottest.ai is an AI-powered chatbot testing tool that focuses on ensuring quality, reliability, and safety in AI-based chatbots. The tool offers automated testing capabilities without the need for coding, making it easy for users to test their chatbots efficiently. With features like regression testing, performance testing, multi-language testing, and AI-powered coverage, bottest.ai provides a comprehensive solution for testing chatbots. Users can record tests, evaluate responses, and improve their chatbots based on analytics provided by the tool. The tool also supports enterprise readiness by allowing scalability, permissions management, and integration with existing workflows.

Kobiton is a mobile device testing platform that accelerates app delivery, improves productivity, and maximizes mobile app impact. It offers a comprehensive suite of features for real-device testing, visual testing, performance testing, accessibility testing, and more. With AI-augmented testing and no-code validations, Kobiton helps enterprises streamline continuous delivery of mobile apps. The platform provides secure and scalable device lab management, mobile device cloud, and integration with DevOps toolchain for enhanced productivity and efficiency.

Mabl is a leading unified test automation platform built on cloud, AI, and low-code innovations that delivers a modern approach ensuring the highest quality software across the entire user journey. Our SaaS platform allows teams to scale functional and non-functional testing across web apps, mobile apps, APIs, performance, and accessibility for best-in-class digital experiences.

Warmy is an AI-powered email deliverability tool that revolutionizes the way emails are sent and received. It offers an all-in-one solution to ensure reliable email channel performance by utilizing cutting-edge AI technology. With features like automated email warming, progress monitoring, perfect email activity, placement checker, and domain performance testing, Warmy helps businesses, marketers, entrepreneurs, and affiliates enhance their email deliverability and reputation. The tool is loved by thousands worldwide and has been verified by G2 and Trustpilot for its effectiveness in improving email deliverability.

Website Builder Hub is an AI-powered website creation platform that offers a user-friendly interface for building professional websites. It provides a range of features such as GPT integration, hiring designers, and discounts on services. The platform aims to help users create visually appealing websites with enhanced SEO capabilities. With a focus on design, customer support, and performance testing, Website Builder Hub assists users in selecting the best website builder for their specific needs.

Sitelifter is an AI-powered website optimization tool that provides actionable insights to improve design, messaging, and user flow. It helps users save time, reduce costs, and maximize conversions by offering AI-driven recommendations tailored to specific goals and audiences. Sitelifter is designed to be user-friendly and accessible for marketers, startups, freelancers, SaaS companies, and anyone looking to enhance their website performance without extensive testing or hiring consultants.

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.

Byterat is a cloud-based platform that provides battery data management, visualization, and analytics. It offers an end-to-end data pipeline that automatically synchronizes, processes, and visualizes materials, manufacturing, and test data from all labs. Byterat also provides 24/7 access to experiments from anywhere in the world and integrates seamlessly with current workflows. It is customizable to specific cell chemistries and allows users to build custom visualizations, dashboards, and analyses. Byterat's AI-powered battery research has been published in leading journals, and its team has pioneered a new class of models that extract tell-tale signals of battery health from electrical signals to forecast future performance.

Keak is the first AI agent designed to continuously improve websites by generating variations through thousands of A/B tests. It automates the process of launching A/B tests, fine-tuning AI models, and self-improving websites. Keak works seamlessly on various platforms and offers a Chrome extension for easy access. With a focus on event tracking and determining winning variations, Keak aims to optimize websites efficiently and effectively.

aqua is a comprehensive Quality Assurance (QA) management tool designed to streamline testing processes and enhance testing efficiency. It offers a wide range of features such as AI Copilot, bug reporting, test management, requirements management, user acceptance testing, and automation management. aqua caters to various industries including banking, insurance, manufacturing, government, tech companies, and medical sectors, helping organizations improve testing productivity, software quality, and defect detection ratios. The tool integrates with popular platforms like Jira, Jenkins, JMeter, and offers both Cloud and On-Premise deployment options. With AI-enhanced capabilities, aqua aims to make testing faster, more efficient, and error-free.

CommandDash is a platform that offers unit, widget, and integration tests for Flutter applications. It was previously known as Welltested AI but is now deprecated. The platform provides developers with the ability to test their Flutter applications thoroughly, ensuring the reliability and functionality of their code.

Giskard is an AI testing platform designed to help companies protect against biases, performance issues, and security risks in AI models. It offers automated detection of issues, compliance with regulations such as the EU AI Act, and unification of AI testing practices. Giskard streamlines the testing process, enhances collaboration between data scientists and business stakeholders, and provides tools for optimal model deployment.

DeepUnit is a software tool designed to facilitate automated unit testing for developers. By utilizing DeepUnit, developers can ensure the quality and reliability of their code by automatically running tests to identify bugs and errors. The tool streamlines the testing process, saving time and effort for developers while improving the overall performance of their software projects. DeepUnit offers a user-friendly interface and seamless integration with popular development environments like NPM and VS Code.

CloudExam AI is an online testing platform developed by Hanke Numerical Union Technology Co., Ltd. It provides stable and efficient AI online testing services, including intelligent grouping, intelligent monitoring, and intelligent evaluation. The platform ensures test fairness by implementing automatic monitoring level regulations and three random strategies. It prioritizes information security by combining software and hardware to secure data and identity. With global cloud deployment and flexible architecture, it supports hundreds of thousands of concurrent users. CloudExam AI offers features like queue interviews, interactive pen testing, data-driven cockpit, AI grouping, AI monitoring, AI evaluation, random question generation, dual-seat testing, facial recognition, real-time recording, abnormal behavior detection, test pledge book, student information verification, photo uploading for answers, inspection system, device detection, scoring template, ranking of results, SMS/email reminders, screen sharing, student fees, and collaboration with selected schools.

The website is an AI tool designed for API privacy, governance, and testing. It offers solutions to detect and remediate sensitive data leaks, ensure compliance, and automate API testing and documentation. The AI-driven platform is trained on 70k public APIs and provides features like AI detection, cataloging, remediation, and best practices for data collection and storage. It aims to streamline API development, enhance performance, and improve security for APIs and applications.

Octomind is an AI-powered Playwright end-to-end testing tool for web applications. It automatically discovers, generates, and runs tests to find bugs before customers do. With features like auto-generating tests, running tests to find bugs, and maintaining tests automatically, Octomind aims to simplify the testing process for developers. It offers real-world wins with testimonials from industry professionals and ensures stability, speed, and a better developer experience. Octomind is built on top of Playwright and can be seamlessly integrated into CI/CD pipelines for continuous testing and monitoring.

CEBRA is a machine-learning method that compresses time series data to reveal hidden structures in the variability of the data. It excels in analyzing behavioral and neural data simultaneously, decoding activity from the visual cortex of the mouse brain to reconstruct viewed videos. CEBRA is a novel encoding method that leverages behavioral and neural data to produce consistent and high-performance latent spaces, allowing for hypothesis testing, label-free usage, and accurate decoding of natural movies from the visual cortex.

Vocera is an AI voice agent testing tool that allows users to test and monitor voice AI agents efficiently. It enables users to launch voice agents in minutes, ensuring a seamless conversational experience. With features like testing against AI-generated datasets, simulating scenarios, and monitoring AI performance, Vocera helps in evaluating and improving voice agent interactions. The tool provides real-time insights, detailed logs, and trend analysis for optimal performance, along with instant notifications for errors and failures. Vocera is designed to work for everyone, offering an intuitive dashboard and data-driven decision-making for continuous improvement.

Teste.ai is an AI-powered platform offering a comprehensive set of software testing tools based on artificial intelligence. It enables users to create test cases, test plans, and step-by-step guides easily from software requirements or documentation. The platform covers functional, usability, performance, security, and API testing, simplifying test data generation and offering specialized prompts for each type of test. Teste.ai aims to streamline the test specification process, optimize tester's time, and enhance testing effectiveness by providing personalized prompts and a variety of testing tools.

The Neutone SDK is a tool designed for researchers to wrap their own audio models and run them in a DAW using the Neutone Plugin. It simplifies the process by allowing models to be built using PyTorch and minimal Python code, eliminating the need for extensive C++ knowledge. The SDK provides support for buffering inputs and outputs, sample rate conversion, and profiling tools for model performance testing. It also offers examples, notebooks, and a submission process for sharing models with the community.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework known for its lightweight design, scalability, and high-speed performance. It offers features like tri-process asynchronous collaboration, Nopad for efficient attention operations, dynamic batch scheduling, FlashAttention integration, tensor parallelism, Token Attention for zero memory waste, and Int8KV Cache. The tool supports various models like BLOOM, LLaMA, StarCoder, Qwen-7b, ChatGLM2-6b, Baichuan-7b, Baichuan2-7b, Baichuan2-13b, InternLM-7b, Yi-34b, Qwen-VL, Llava-7b, Mixtral, Stablelm, and MiniCPM. Users can deploy and query models using the provided server launch commands and interact with multimodal models like QWen-VL and Llava using specific queries and images.

Eval-Scope is a framework designed to support the evaluation of large language models (LLMs) by providing pre-configured benchmark datasets, common evaluation metrics, model integration, automatic evaluation for objective questions, complex task evaluation using expert models, reports generation, visualization tools, and model inference performance evaluation. It is lightweight, easy to customize, supports new dataset integration, model hosting on ModelScope, deployment of locally hosted models, and rich evaluation metrics. Eval-Scope also supports various evaluation modes like single mode, pairwise-baseline mode, and pairwise (all) mode, making it suitable for assessing and improving LLMs.

awesome-AIOps is a curated list of academic researches and industrial materials related to Artificial Intelligence for IT Operations (AIOps). It includes resources such as competitions, white papers, blogs, tutorials, benchmarks, tools, companies, academic materials, talks, workshops, papers, and courses covering various aspects of AIOps like anomaly detection, root cause analysis, incident management, microservices, dependency tracing, and more.

AgentOps is a toolkit for evaluating and developing robust and reliable AI agents. It provides benchmarks, observability, and replay analytics to help developers build better agents. AgentOps is open beta and can be signed up for here. Key features of AgentOps include: - Session replays in 3 lines of code: Initialize the AgentOps client and automatically get analytics on every LLM call. - Time travel debugging: (coming soon!) - Agent Arena: (coming soon!) - Callback handlers: AgentOps works seamlessly with applications built using Langchain and LlamaIndex.

aioapns is a Python library designed for sending push-notifications to iOS devices via Apple Push Notification Service. It provides an efficient client through asynchronous HTTP2 protocol for use with Python's asyncio framework. With features like internal connection pool, support for different types of connections, setting TTL and priority for notifications, and more, aioapns is a versatile tool for developers looking to send push notifications to iOS devices.

AIStore is a lightweight object storage system designed for AI applications. It is highly scalable, reliable, and easy to use. AIStore can be deployed on any commodity hardware, and it can be used to store and manage large datasets for deep learning and other AI applications.

AI Verify is an AI governance testing framework and software toolkit that validates the performance of AI systems against internationally recognised principles through standardised tests. It offers a new API Connector feature to bypass size limitations, test various AI frameworks, and configure connection settings for batch requests. The toolkit operates within an enterprise environment, conducting technical tests on common supervised learning models for tabular and image datasets. It does not define AI ethical standards or guarantee complete safety from risks or biases.

AI Verify is an AI governance testing framework and software toolkit that validates the performance of AI systems against a set of internationally recognised principles through standardised tests. AI Verify is consistent with international AI governance frameworks such as those from European Union, OECD and Singapore. It is a single integrated toolkit that operates within an enterprise environment. It can perform technical tests on common supervised learning classification and regression models for most tabular and image datasets. It however does not define AI ethical standards and does not guarantee that any AI system tested will be free from risks or biases or is completely safe.

This repository contains code and data for replicating experiments on Long-Term Memory (LTM) abilities of conversational agents. It includes a benchmark for testing agents' memory performance over long conversations, evaluating tasks requiring dynamic memory upkeep and information integration. The repository supports various models, datasets, and configurations for benchmarking and reporting results.

GuideLLM is a powerful tool for evaluating and optimizing the deployment of large language models (LLMs). By simulating real-world inference workloads, GuideLLM helps users gauge the performance, resource needs, and cost implications of deploying LLMs on various hardware configurations. This approach ensures efficient, scalable, and cost-effective LLM inference serving while maintaining high service quality. Key features include performance evaluation, resource optimization, cost estimation, and scalability testing.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

FlagPerf is an integrated AI hardware evaluation engine jointly built by the Institute of Intelligence and AI hardware manufacturers. It aims to establish an industry-oriented metric system to evaluate the actual capabilities of AI hardware under software stack combinations (model + framework + compiler). FlagPerf features a multidimensional evaluation metric system that goes beyond just measuring 'whether the chip can support specific model training.' It covers various scenarios and tasks, including computer vision, natural language processing, speech, multimodal, with support for multiple training frameworks and inference engines to connect AI hardware with software ecosystems. It also supports various testing environments to comprehensively assess the performance of domestic AI chips in different scenarios.

The 'farel-bench' project is a benchmark tool for testing LLM reasoning abilities with family relationship quizzes. It generates quizzes based on family relationships of varying degrees and measures the accuracy of large language models in solving these quizzes. The project provides scripts for generating quizzes, running models locally or via APIs, and calculating benchmark metrics. The quizzes are designed to test logical reasoning skills using family relationship concepts, with the goal of evaluating the performance of language models in this specific domain.

LLM Hallucination Index - RAG Special is a comprehensive evaluation of large language models (LLMs) focusing on context length and open vs. closed-source attributes. The index explores the impact of context length on model performance and tests the assumption that closed-source LLMs outperform open-source ones. It also investigates the effectiveness of prompting techniques like Chain-of-Note across different context lengths. The evaluation includes 22 models from various brands, analyzing major trends and declaring overall winners based on short, medium, and long context insights. Methodologies involve rigorous testing with different context lengths and prompting techniques to assess models' abilities in handling extensive texts and detecting hallucinations.

Athina is an open-source library designed to help engineers improve the reliability and performance of Large Language Models (LLMs) through eval-driven development. It offers plug-and-play preset evals for catching and preventing bad outputs, measuring model performance, running experiments, A/B testing models, detecting regressions, and monitoring production data. Athina provides a solution to the flaws in current LLM developer workflows by offering rapid experimentation, customizable evaluators, integrated dashboard, consistent metrics, historical record tracking, and easy setup. It includes preset evaluators for RAG applications and summarization accuracy, as well as the ability to write custom evals. Athina's evals can run on both development and production environments, providing consistent metrics and removing the need for manual infrastructure setup.

Linesight is a reinforcement learning project focused on advancing AI capabilities in the racing game Trackmania. It aims to push the boundaries of AI performance by utilizing deep learning algorithms to achieve human-level driving and beat world records on official campaign tracks. The project provides an interface to interact with Trackmania Nations Forever programmatically, enabling tasks such as sending inputs, retrieving car states, and capturing screenshots. With a strong emphasis on equality of input devices, Linesight serves as a benchmark for testing various reinforcement learning algorithms in a challenging and dynamic gaming environment.

Ensures software performance meets organizational standards and expectations.

Expert in software performance testing and optimization 📊

It's time to crawl your website, it's time to test your code!

Assists in writing React Native tests using the React Native Testing Library.

This GPT takes in content related to an application, such as HTTP traffic, JavaScript files, source code, etc., and outputs lists of URLs that can be used for further testing.

IQ Test is designed to simulate an IQ testing environment. It provides a formal and objective experience, delivering questions and processing answers in a straightforward manner.

Expert in ads incrementality and campaign will help you interpret data, forecasting and share you testing frameworks using advanced Python libraries

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A formal, expert guide for DevOps pros advancing their skills. Your DevOps GYM

Senior TypeScript Programmer with expertise in Node.js, React, and Redux.

Optimize Website Landing Page Conversion Rates. You will use the advice in the provided knowledge base to help optimize website conversion rates. The user can upload screenshots of the landing page and you'll use the knowledge provided to your to recommend the best possible courses of action.

Upload your SAT score PDF to our calculator and analyze how you did and how to preform better

I test and optimize your code snippets.

Expert on computing performance, inspired by Brendan Gregg.

A career coach aiding in writing self-evaluations.

Drives financial performance improvement via strategic analysis and advice.

Optimizes financial performance through strategic analysis and planning.

Expert en optimisation de performance et traitement de données

I'm your go-to for sports analysis and visualisations.

Enthusiastic Java code optimizer with a focus on clarity and encouragement.