Best AI tools for< Qa Lead >

Sofy is a revolutionary no-code testing platform for mobile applications that integrates AI to streamline the testing process. It offers features such as manual and ad-hoc testing, no-code automation, AI-powered test case generation, and real device testing. Sofy helps app development teams achieve high-quality releases by simplifying test maintenance and ensuring continuous precision. With a focus on efficiency and user experience, Sofy is trusted by top industries for its all-in-one testing solution.

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.

Functionize is an AI-powered test automation platform that helps enterprises improve their product quality and release faster. It uses machine learning to automate test creation, maintenance, and execution, and provides a range of features to help teams collaborate and manage their testing process. Functionize integrates with popular CI/CD tools and DevOps pipelines, and offers a range of pricing options to suit different needs.

Diffblue Cover is an autonomous AI-powered unit test writing tool for Java development teams. It uses next-generation autonomous AI to automate unit testing, freeing up developers to focus on more creative work. Diffblue Cover can write a complete and correct Java unit test every 2 seconds, and it is directly integrated into CI pipelines, unlike AI-powered code suggestions that require developers to check the code for bugs. Diffblue Cover is trusted by the world's leading organizations, including Goldman Sachs, and has been proven to improve quality, lower developer effort, help with code understanding, reduce risk, and increase deployment frequency.

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.

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.

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.

Codeway is a leading mobile AI app developer that actively supports earthquake relief efforts in Turkey. With a focus on creating AI-powered apps, Codeway leverages cutting-edge AI technologies to deliver unparalleled user experiences. The company invests in R&D operations to ensure excellence in technology implementation, and is committed to understanding user needs for continuous app evolution. Codeway's products include mobile apps like Cleanup, Scanner+, Ask AI, Facedance, Wonder, Rumble Rivals, and PixelUp. The company excels in marketing, product management, and culture, attracting top talent and fostering a data-driven roadmap to success.

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.

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.

Cresta AI is an enterprise-grade Gen AI platform designed for the contact center, offering a suite of intelligent products that analyze conversations, provide real-time guidance to agents, and drive transformative results for Fortune 500 companies. The platform leverages generative AI to deliver targeted automation, personalized coaching, and AI-native management solutions, all trained on the user's data. Cresta's no-code command center empowers non-technical leaders to deploy AI models effortlessly, ensuring businesses can adapt and evolve seamlessly. With a focus on enhancing sales, customer care, retention, and collections processes, Cresta aims to revolutionize contact center operations with cutting-edge AI technology.

Interview.study is an AI-powered interview preparation platform that helps candidates practice real interview questions asked by top companies. The platform provides users with instant feedback on their responses, helping them identify areas for improvement and develop stronger answers. Interview.study also offers a variety of features to help candidates prepare for their interviews, including a database of interview questions, a mock interview tool, and a resume builder.

RoboResponseAI is a proactive AI chatbot customized for businesses, designed to initiate conversations, take feedback, and drive lead conversions. It offers features such as lead conversion guidance, recruitment assistance, quick chatbot training, interactive ad campaigns, and seamless integration with various platforms. The application aims to enhance customer engagement, streamline support processes, and improve lead generation for businesses of all types.

PackPack is an AI-driven bookmarking tool that allows users to save various types of content with just one click. It offers features like saving articles, social media posts, e-commerce products, videos, and audios, as well as providing relevant search results and AI-powered functions for summarizing content, analyzing images, and recognizing subtitles. Users can organize their saved content into collections and easily share them. PackPack is trusted by industry leaders and offers a distraction-free reading experience with no ads or pop-ups.

AI Sidekick is a team analytics tool powered by ChatGPT, integrated within Slack to provide actionable insights from daily Q&A sessions. It acts as an all-knowing Executive Assistant, streamlining communication and decision-making processes within teams. By leveraging AI technology, AI Sidekick aims to enhance team productivity, identify and resolve blockers efficiently, and improve overall team morale.

1440.io is an Omnichannel Engagement Suite designed for Salesforce, offering a comprehensive set of tools to streamline customer engagement across various channels. It enables businesses to unify conversations across the customer journey, leverage AI-powered chatbots, personalize interactions, and optimize contact centers. The platform is trusted by leading enterprise brands and aims to improve time-to-value by maximizing the 1440 minutes we all have each day. With features like messaging studio, translation studio, reputation studio, and commerce studio, 1440.io empowers customer-facing teams to deliver premium experiences and drive sales through conversational commerce.

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.

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.

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.

Zebrunner is an AI-powered unified platform for manual and automated testing, designed to synchronize manual and automation QA teams in one place. It offers features such as test management, automation reporting, and test case management, with capabilities for generating new test cases, autocomplete existing ones, and categorize failures using AI. Zebrunner provides a clean and intuitive UI, unmatched performance, powerful reporting, rich integrations, and 24/7 support for efficient testing processes. It also offers customizable dashboards, sharable reports, and seamless integrations with Jira and other SDLC tools for streamlined workflows.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.

This repository contains executable Python notebooks, sample apps, and resources for testing out the Elastic platform. Users can learn how to use Elasticsearch as a vector database for storing embeddings, build use cases like retrieval augmented generation (RAG), summarization, and question answering (QA), and test Elastic's leading-edge capabilities like the Elastic Learned Sparse Encoder and reciprocal rank fusion (RRF). It also allows integration with projects like OpenAI, Hugging Face, and LangChain to power LLM-powered applications. The repository enables modern search experiences powered by AI/ML.

MME-RealWorld is a benchmark designed to address real-world applications with practical relevance, featuring 13,366 high-resolution images and 29,429 annotations across 43 tasks. It aims to provide substantial recognition challenges and overcome common barriers in existing Multimodal Large Language Model benchmarks, such as small data scale, restricted data quality, and insufficient task difficulty. The dataset offers advantages in data scale, data quality, task difficulty, and real-world utility compared to existing benchmarks. It also includes a Chinese version with additional images and QA pairs focused on Chinese scenarios.

ShapeLLM is the first 3D Multimodal Large Language Model designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages. It supports single-view colored point cloud input and introduces a robust 3D QA benchmark, 3D MM-Vet, encompassing various variants. The model extends the powerful point encoder architecture, ReCon++, achieving state-of-the-art performance across a range of representation learning tasks. ShapeLLM can be used for tasks such as training, zero-shot understanding, visual grounding, few-shot learning, and zero-shot learning on 3D MM-Vet.

TempCompass is a benchmark designed to evaluate the temporal perception ability of Video LLMs. It encompasses a diverse set of temporal aspects and task formats to comprehensively assess the capability of Video LLMs in understanding videos. The benchmark includes conflicting videos to prevent models from relying on single-frame bias and language priors. Users can clone the repository, install required packages, prepare data, run inference using examples like Video-LLaVA and Gemini, and evaluate the performance of their models across different tasks such as Multi-Choice QA, Yes/No QA, Caption Matching, and Caption Generation.

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.

LongCite is a tool that enables Large Language Models (LLMs) to generate fine-grained citations in long-context Question Answering (QA) scenarios. It provides models trained on GLM-4-9B and Meta-Llama-3.1-8B, supporting up to 128K context. Users can deploy LongCite chatbots, generate accurate responses, and obtain precise sentence-level citations. The tool includes components for model deployment, Coarse to Fine (CoF) pipeline for data construction, model training using LongCite-45k dataset, evaluation with LongBench-Cite benchmark, and citation generation.

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) based on InternLM2-7B excelling in free-form text-image composition and comprehension. It boasts several amazing capabilities and applications: * **Free-form Interleaved Text-Image Composition** : InternLM-XComposer2 can effortlessly generate coherent and contextual articles with interleaved images following diverse inputs like outlines, detailed text requirements and reference images, enabling highly customizable content creation. * **Accurate Vision-language Problem-solving** : InternLM-XComposer2 accurately handles diverse and challenging vision-language Q&A tasks based on free-form instructions, excelling in recognition, perception, detailed captioning, visual reasoning, and more. * **Awesome performance** : InternLM-XComposer2 based on InternLM2-7B not only significantly outperforms existing open-source multimodal models in 13 benchmarks but also **matches or even surpasses GPT-4V and Gemini Pro in 6 benchmarks** We release InternLM-XComposer2 series in three versions: * **InternLM-XComposer2-4KHD-7B** 🤗: The high-resolution multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _High-resolution understanding_ , _VL benchmarks_ and _AI assistant_. * **InternLM-XComposer2-VL-7B** 🤗 : The multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _VL benchmarks_ and _AI assistant_. **It ranks as the most powerful vision-language model based on 7B-parameter level LLMs, leading across 13 benchmarks.** * **InternLM-XComposer2-VL-1.8B** 🤗 : A lightweight version of InternLM-XComposer2-VL based on InternLM-1.8B. * **InternLM-XComposer2-7B** 🤗: The further instruction tuned VLLM for _Interleaved Text-Image Composition_ with free-form inputs. Please refer to Technical Report and 4KHD Technical Reportfor more details.

VideoLLaMA 2 is a project focused on advancing spatial-temporal modeling and audio understanding in video-LLMs. It provides tools for multi-choice video QA, open-ended video QA, and video captioning. The project offers model zoo with different configurations for visual encoder and language decoder. It includes training and evaluation guides, as well as inference capabilities for video and image processing. The project also features a demo setup for running a video-based Large Language Model web demonstration.

MiniCPM is a series of open-source large models on the client side jointly developed by Face Intelligence and Tsinghua University Natural Language Processing Laboratory. The main language model MiniCPM-2B has only 2.4 billion (2.4B) non-word embedding parameters, with a total of 2.7B parameters. - After SFT, MiniCPM-2B performs similarly to Mistral-7B on public comprehensive evaluation sets (better in Chinese, mathematics, and code capabilities), and outperforms models such as Llama2-13B, MPT-30B, and Falcon-40B overall. - After DPO, MiniCPM-2B also surpasses many representative open-source large models such as Llama2-70B-Chat, Vicuna-33B, Mistral-7B-Instruct-v0.1, and Zephyr-7B-alpha on the current evaluation set MTBench, which is closest to the user experience. - Based on MiniCPM-2B, a multi-modal large model MiniCPM-V 2.0 on the client side is constructed, which achieves the best performance of models below 7B in multiple test benchmarks, and surpasses larger parameter scale models such as Qwen-VL-Chat 9.6B, CogVLM-Chat 17.4B, and Yi-VL 34B on the OpenCompass leaderboard. MiniCPM-V 2.0 also demonstrates leading OCR capabilities, approaching Gemini Pro in scene text recognition capabilities. - After Int4 quantization, MiniCPM can be deployed and inferred on mobile phones, with a streaming output speed slightly higher than human speech speed. MiniCPM-V also directly runs through the deployment of multi-modal large models on mobile phones. - A single 1080/2080 can efficiently fine-tune parameters, and a single 3090/4090 can fully fine-tune parameters. A single machine can continuously train MiniCPM, and the secondary development cost is relatively low.

This repository contains the code for LongRAG, a framework that enhances retrieval-augmented generation with long-context LLMs. LongRAG introduces a 'long retriever' and a 'long reader' to improve performance by using a 4K-token retrieval unit, offering insights into combining RAG with long-context LLMs. The repo provides instructions for installation, quick start, corpus preparation, long retriever, and long reader.

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.

This repository contains language models for the Russian language, as well as their implementation and comparison. The models are trained on a dataset of ChatGPT-generated instructions and chats in Russian. They can be used for a variety of tasks, including question answering, text generation, and translation.

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.

BABILong is a generative benchmark designed to evaluate the performance of NLP models in processing long documents with distributed facts. It consists of 20 tasks that simulate interactions between characters and objects in various locations, requiring models to distinguish important information from irrelevant details. The tasks vary in complexity and reasoning aspects, with test samples potentially containing millions of tokens. The benchmark aims to challenge and assess the capabilities of Large Language Models (LLMs) in handling complex, long-context information.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

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.

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This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

Designed for excellence in Quality Assurance, fine-tuning custom GPT configurations through continuous refinement.

測試用：引用 OMP YouTube vidoe 回答 Zapier 問題

你是一个问答对生成器，你可以对下面给定上下文的主要内容进行概括和提炼，并按照下面给定的生成规则去生成。

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

I provide Automation QA interview prep and conduct mock interviews.

I provide Manual QA interview prep and conduct mock interviews.

I will provide guidance on testing, verification, and validation for QA roles.

A Smart QA Bot

Enhanced QA/QC expertise with user-driven improvements, powered by OpenAI

A helpful QA bot for Bubble no-code tool learners.

Expert in localizing & QA'ing content with Excel-friendly output.

QA4AI Guidelines GPT

Expert in Selenium test automation, providing practical advice and solutions.

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

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

Guides in creating or improving BDD scenarios

Help with generating unit tests using Spock framework

Fully-equipped .har file inspector with image extraction

Algorithm-focused test case generator.

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