Best AI tools for< Improve Qa Efficiency >

QA.tech is an advanced end-to-end testing application designed for B2B SaaS companies. It offers AI-powered testing solutions to help businesses ship faster, cut costs, and improve testing efficiency. The application features an AI agent named Jarvis that automates the testing process by scanning web apps, creating detailed memory structures, generating tests based on user interactions, and continuously testing for defects. QA.tech provides developer-friendly bug reports, supports various web frameworks, and integrates with CI/CD pipelines. It aims to revolutionize the testing process by offering faster, smarter, and more efficient testing solutions.

TheLoops is an AI platform designed for Customer Experience (CX) operations, offering a range of AI-powered solutions to enhance agent efficiency, improve customer satisfaction, and streamline processes. The platform integrates with various applications, provides predictive analytics, automates tasks, and offers real-time insights to optimize CX operations. TheLoops is trusted by leading SaaS companies and aims to redefine processes, empower teams, and transform outcomes with efficiency.

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.

Supertest is an AI copilot designed for software testing, offering a cutting-edge solution to automate various day-to-day QA engineering tasks using AI technology. With Supertest, users can easily generate unit tests, integrate with VS Code, and streamline their testing processes. The tool aims to revolutionize the way software testing is conducted by providing a seamless and efficient testing experience.

Chatlas is a powerful AI chatbot application designed to revolutionize customer communication on websites. It offers advanced algorithms for indexing website content, customizable conversations, 24/7 availability, and the ability to upload documents and conduct Q&A sessions to train the chatbot. Chatlas aims to enhance customer engagement, streamline support processes, and provide an interactive website experience through intelligent automation.

Tettra is an AI-powered knowledge management system designed to help organizations curate company information into an internal knowledge base, instantly answer team questions with AI in Slack or the app, save reusable answers with automation, and streamline onboarding processes. It offers features like internal Q&A, knowledge management system, Slack integration, CSAT notifications, and integrations with SupportMan. Tettra is trusted by various teams to organize scattered knowledge and improve efficiency by eliminating bottlenecks and saving time from repetitive questions.

moyoNote is an AI-powered tool designed for organizing, managing, and structuring information into a comprehensive knowledge base. It offers features such as generating mind maps from text or files, interactive Q&A for maps, and customization options for personal expression. Users can easily share mind maps with others and control access permissions. The tool aims to simplify workflow, improve work efficiency, and enhance collaboration among users.

Virtuoso is an AI-powered, end-to-end functional testing tool for web applications. It uses Natural Language Programming, Machine Learning, and Robotic Process Automation to automate the testing process, making it faster and more efficient. Virtuoso can be used by QA managers, practitioners, and senior executives to improve the quality of their software applications.

Loris is a conversational intelligence platform designed for leading brands to unlock the hidden value of every customer conversation. It combines proven machine learning and generative AI to provide industry-leading conversation intelligence. Loris helps customer service teams be more efficient, improve customer experience, and drive revenue growth by transforming customer conversations into actionable insights. The platform offers features such as automated quality assurance, real-time agent co-pilot, and customer insights to enhance agent performance and increase customer satisfaction.

Whybug is an AI tool designed to help developers troubleshoot and fix coding errors efficiently. By leveraging a large language model trained on data from StackExchange and other sources, Whybug can analyze error messages, identify root causes, and provide suggestions for resolution. Users can simply paste an error message into the tool and receive detailed explanations and example fixes. With Whybug, developers can streamline the debugging process and improve code quality.

AI Generated Test Cases is an innovative tool that leverages artificial intelligence to automatically generate test cases for software applications. By utilizing advanced algorithms and machine learning techniques, this tool can efficiently create a comprehensive set of test scenarios to ensure the quality and reliability of software products. With AI Generated Test Cases, software development teams can save time and effort in the testing phase, leading to faster release cycles and improved overall productivity.

Merchynt is an AI-powered Google Business Profile management software that helps businesses optimize their Google My Business profiles efficiently. It offers features such as automated posts, Q&A management, image uploads, and review management. With Merchynt, businesses can rank higher on Google Maps and the 'Map Pack' on Google Search. The software is trained on the business's information and continuously improves over time, providing a fully automated solution for local SEO optimization.

Autify is an AI testing company focused on solving challenges in automation testing. They aim to make software testing faster and easier, enabling companies to release faster and maintain application stability. Their flagship product, Autify No Code, allows anyone to create automated end-to-end tests for applications. Zenes, their new product, simplifies the process of creating new software tests through AI. Autify is dedicated to innovation in the automation testing space and is trusted by leading organizations.

SQM Group's mySQM™ QA software is a comprehensive solution for call centers to monitor, motivate, and manage agents, ultimately improving customer experience (CX) and reducing QA costs by 50%. It combines three data sources: post-call surveys, call handling data, and call compliance feedback, providing holistic CX insights. The software offers personalized agent self-coaching suggestions, real-time recognition for great CX delivery, and benchmarks, ranks, awards, and certifies Csat, FCR, and QA performance.

MaestroQA is a comprehensive Call Center Quality Assurance Software that offers a range of products and features to enhance QA processes. It provides customizable report builders, scorecard builders, calibration workflows, coaching workflows, automated QA workflows, screen capture, accurate transcriptions, root cause analysis, performance dashboards, AI grading assist, analytics, and integrations with various platforms. The platform caters to industries like eCommerce, financial services, gambling, insurance, B2B software, social media, and media, offering solutions for QA managers, team leaders, and executives.

Mobot is an AI-powered platform that offers end-to-end mobile automation solutions. It utilizes AI-driven mechanical robots to automate critical aspects of the mobile ecosystem, enabling faster releases, fewer issues, and significant time and cost savings for engineering, product, and growth teams. Mobot provides managed and self-service mobile testing for engineering and marketing purposes, mobile campaign monitoring, integrations with favorite apps, and supports various use cases. The platform caters to different teams such as engineering, QA, product, marketing, and support, helping them achieve 100% testing coverage and streamline their workflows.

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.

ILoveMyQA is an AI-powered QA testing service that provides comprehensive, well-documented bug reports. The service is affordable, easy to get started with, and requires no time-zapping chats. ILoveMyQA's team of Rockstar QAs is dedicated to helping businesses find and fix bugs before their customers do, so they can enjoy the results and benefits of having a QA team without the cost, management, and headaches.

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.

Spur is an AI QA tool that allows users to test websites using natural language, eliminating the need for complex test scripts. It offers reliable automated tests that adapt to UI changes, real-time playback for debugging, and powerful validations. Spur's AI-powered tests reduce manual testing time, improve software testing processes, and ensure the reliability of tests even with site changes. The tool is user-friendly, requires no coding skills, and supports API testing.

MInference is a tool designed to accelerate pre-filling for long-context Language Models (LLMs) by leveraging dynamic sparse attention. It achieves up to a 10x speedup for pre-filling on an A100 while maintaining accuracy. The tool supports various decoding LLMs, including LLaMA-style models and Phi models, and provides custom kernels for attention computation. MInference is useful for researchers and developers working with large-scale language models who aim to improve efficiency without compromising accuracy.

AppBuilder SDK is a one-stop development tool for AI native applications, providing basic cloud resources, AI capability engine, Qianfan large model, and related capability components to improve the development efficiency of AI native applications.

DriveLM is a multimodal AI model that enables autonomous driving by combining computer vision and natural language processing. It is designed to understand and respond to complex driving scenarios using visual and textual information. DriveLM can perform various tasks related to driving, such as object detection, lane keeping, and decision-making. It is trained on a massive dataset of images and text, which allows it to learn the relationships between visual cues and driving actions. DriveLM is a powerful tool that can help to improve the safety and efficiency of autonomous vehicles.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

SLMs-Survey is a comprehensive repository that includes papers and surveys on small language models. It covers topics such as technology, on-device applications, efficiency, enhancements for LLMs, and trustworthiness. The repository provides a detailed overview of existing SLMs, their architecture, enhancements, and specific applications in various domains. It also includes information on SLM deployment optimization techniques and the synergy between SLMs and LLMs.

Arbigent (Arbiter-Agent) is an AI agent testing framework designed to make AI agent testing practical for modern applications. It addresses challenges faced by traditional UI testing frameworks and AI agents by breaking down complex tasks into smaller, dependent scenarios. The framework is customizable for various AI providers, operating systems, and form factors, empowering users with extensive customization capabilities. Arbigent offers an intuitive UI for scenario creation and a powerful code interface for seamless test execution. It supports multiple form factors, optimizes UI for AI interaction, and is cost-effective by utilizing models like GPT-4o mini. With a flexible code interface and open-source nature, Arbigent aims to revolutionize AI agent testing in modern applications.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

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)

Parlant is a structured approach to building and guiding customer-facing AI agents. It allows developers to create and manage robust AI agents, providing specific feedback on agent behavior and helping understand user intentions better. With features like guidelines, glossary, coherence checks, dynamic context, and guided tool use, Parlant offers control over agent responses and behavior. Developer-friendly aspects include instant changes, Git integration, clean architecture, and type safety. It enables confident deployment with scalability, effective debugging, and validation before deployment. Parlant works with major LLM providers and offers client SDKs for Python and TypeScript. The tool facilitates natural customer interactions through asynchronous communication and provides a chat UI for testing new behaviors before deployment.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

MiniCPM-V is a series of end-side multimodal LLMs designed for vision-language understanding. The models take image and text inputs to provide high-quality text outputs. The series includes models like MiniCPM-Llama3-V 2.5 with 8B parameters surpassing proprietary models, and MiniCPM-V 2.0, a lighter model with 2B parameters. The models support over 30 languages, efficient deployment on end-side devices, and have strong OCR capabilities. They achieve state-of-the-art performance on various benchmarks and prevent hallucinations in text generation. The models can process high-resolution images efficiently and support multilingual capabilities.

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

The collection is actively updated with the help of an internal literature search engine.

Advises on QA tests based on recent game code changes, including git history. Learn more at regression.gg

Ensures efficient software updates through continuous integration and deployment.

I provide Manual QA interview prep and conduct mock interviews.

Makes every Sofware Tester an Expert Prompt Engineer

The official GPT for the MegaMock library

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

I write unit tests for uploaded Dynamics 365 C# code files.

Test Shaman: Guiding software testing with Grug wisdom and humor, balancing fun with practical advice.

I craft tests first, then code, validating new features.

Your test-driven coding tutor.

I write tests that make bugs think twice.

专注于全流程黑盒测试的Scala TDD专家

Friendly expert on mobile accessibility, offering concise, value-focused advice.

Ensures product quality through rigorous, systematic testing processes.

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

Günlük soruları çöz ve rekabete katıl. Kendi soru-cevap setini oluştur, oyuncuların oluşturduğu eğlenceli soruları çöz.

Helps you close usability cases in no time

Friendly assistant for React app testing, detailed and accessible.

Drop your requirements here and we'll Simply input, analyze, and refine for corner case detection!

Clone and replicate the source site using a screenshot, while enabling continuous development and optimization capabilities. - 通过截图复制源站点前端代码，同时具备持续开发和优化功能。Any Issue: contact me @X: https://twitter.com/tb_xy09