Best AI tools for< Evaluate System Performance >

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.

SiMa.ai is an AI application that offers high-performance, power-efficient, and scalable edge machine learning solutions for various industries such as automotive, industrial, healthcare, drones, and government sectors. The platform provides MLSoC™ boards, DevKit 2.0, Palette Software 1.2, and Edgematic™ for developers to accelerate complete applications and deploy AI-enabled solutions. SiMa.ai's Machine Learning System on Chip (MLSoC) enables full-pipeline implementations of real-world ML solutions, making it a trusted platform for edge AI development.

Compassionate AI is a cutting-edge AI-powered platform that empowers individuals and organizations to create and deploy AI solutions that are ethical, responsible, and aligned with human values. With Compassionate AI, users can access a comprehensive suite of tools and resources to design, develop, and implement AI systems that prioritize fairness, transparency, and accountability.

Workable is a leading recruiting software and hiring platform that offers a full Applicant Tracking System with built-in AI sourcing. It provides a configurable HRIS platform to securely manage employees, automate hiring tasks, and offer actionable insights and reporting. Workable helps companies streamline their recruitment process, from sourcing to employee onboarding and management, with features like sourcing and attracting candidates, evaluating and collaborating with hiring teams, automating hiring tasks, onboarding and managing employees, and tracking HR processes.

Mangus is an AI-powered learning platform that provides personalized learning paths for employees and students. It offers a wide range of courses and programs in various disciplines, including business, education, technology, and more. Mangus uses gamification and artificial intelligence to create an engaging and effective learning experience.

Flow AI is an advanced AI tool designed for evaluating and improving Large Language Model (LLM) applications. It offers a unique system for creating custom evaluators, deploying them with an API, and developing specialized LMs tailored to specific use cases. The tool aims to revolutionize AI evaluation and model development by providing transparent, cost-effective, and controllable solutions for AI teams across various domains.

PyjamaHR is a leading AI-powered Applicant Tracking System (ATS) and recruitment software designed to streamline the hiring process for businesses of all sizes. It offers advanced features such as source management, candidate evaluation, collaboration tools, and AI-powered candidate tests to enhance the efficiency and effectiveness of the recruitment process. With a user-friendly interface and robust security measures, PyjamaHR is a trusted solution for managing talent acquisition and improving hiring outcomes.

Recooty is a modern applicant tracking system designed for growing companies to streamline their recruiting process. It offers features such as applicant tracking, job posting, candidate tracking, interview scheduling, talent pool management, employer branding, and HR tools. With Recooty, companies can attract, engage, and hire their next teammates with ease. The platform also provides resources like job descriptions, templates, interview questions, and AI tools to enhance the recruitment experience.

PolygrAI is a digital polygraph powered by AI technology that provides real-time risk assessment and sentiment analysis. The platform meticulously analyzes facial micro-expressions, body language, vocal attributes, and linguistic cues to detect behavioral fluctuations and signs of deception. By combining well-established psychology practices with advanced AI and computer vision detection, PolygrAI offers users actionable insights for decision-making processes across various applications.

Wizi AI is a technical AI interviewer that helps employers evaluate hundreds of candidates with in-depth assessments. It goes beyond basic coding challenges and conducts an onsite interview experience for every candidate. Employers get actionable hiring signals with in-depth reports on system design, project implementation, domain expertise, and debugging skills. Wizi AI saves teams time by screening all candidates with AI and bringing only the best to onsites.

Sacred is a tool to configure, organize, log and reproduce computational experiments. It is designed to introduce only minimal overhead, while encouraging modularity and configurability of experiments. The ability to conveniently make experiments configurable is at the heart of Sacred. If the parameters of an experiment are exposed in this way, it will help you to: keep track of all the parameters of your experiment easily run your experiment for different settings save configurations for individual runs in files or a database reproduce your results In Sacred we achieve this through the following main mechanisms: Config Scopes are functions with a @ex.config decorator, that turn all local variables into configuration entries. This helps to set up your configuration really easily. Those entries can then be used in captured functions via dependency injection. That way the system takes care of passing parameters around for you, which makes using your config values really easy. The command-line interface can be used to change the parameters, which makes it really easy to run your experiment with modified parameters. Observers log every information about your experiment and the configuration you used, and saves them for example to a Database. This helps to keep track of all your experiments. Automatic seeding helps controlling the randomness in your experiments, such that they stay reproducible.

NexLev is an AI-powered YouTube niche finder that helps users discover untapped, high-demand niches in seconds. It provides detailed YouTube channel analytics and an intuitive filtering system, making it easier for users to find lucrative niches for their next YouTube venture. NexLev also offers a variety of features such as a keyword analysis tool, competitor analysis, and a niche profitability calculator.

Applicant AI is an applicant tracking and recruiting software powered by AI (ATS). It helps companies review job applicants 10x faster by using AI to screen thousands of applicants and identify the right candidates in seconds. The tool transforms the traditional applicant selection process, saving users 80% of the time spent on screening. With features like AI-generated summaries, ratings, and custom instructions evaluation, Applicant AI streamlines the hiring process and ensures only high-quality applicants are considered. The platform is compliant with EU AI regulation, prioritizes human decision-making, and aims to minimize risks of unfair or biased outcomes in employment.

Notle is an advanced AI-driven psychometric recording tool designed for mental health professionals. It revolutionizes how patient interactions in psychotherapy sessions are captured and analyzed. The platform provides cutting-edge analysis, effortless tracking, in-depth metrics, and empowers clinicians with intelligent analytics for personalized care. Notle sets a new benchmark for psychometric evaluation tools, ensuring unrivaled precision in psychometric assessment. It offers advanced behavioral insights, user-friendly interface, unmatched precision & reliability, and non-invasive integration into healthcare practices. The application is reliable, accurate, impactful, and validated through research methods.

Questflow is a decentralized AI agent economy platform that enables users to orchestrate multiple AI agents to gather insights, take action, and earn rewards autonomously. It serves as a co-pilot for work, helping knowledge workers automate repetitive tasks in a private, safety-first approach. The platform offers features such as multi-agent orchestration, user-friendly dashboard, visual reports, smart keyword generator, content evaluation, SEO goal setting, automated alerts, actionable SEO tips, regular SEO goal setting, and link optimization wizard.

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

LlamaIndex is a framework for building context-augmented Large Language Model (LLM) applications. It provides tools to ingest and process data, implement complex query workflows, and build applications like question-answering chatbots, document understanding systems, and autonomous agents. LlamaIndex enables context augmentation by combining LLMs with private or domain-specific data, offering tools for data connectors, data indexes, engines for natural language access, chat engines, agents, and observability/evaluation integrations. It caters to users of all levels, from beginners to advanced developers, and is available in Python and Typescript.

The website offers a service where users can have their resumes analyzed by an AI system. Users can submit their resumes to receive feedback and suggestions for improvement. The AI tool evaluates various aspects of the resume, such as formatting, content, and relevance to the job market. It aims to help users enhance their resumes to increase their chances of landing job interviews.

MailMaestro is an AI email assistant that helps users write better emails faster, allowing them to be more productive and focus on important tasks. The company behind MailMaestro, Maestro Labs, acquired Flowrite, the AI writing division of Flow AI, in September 2024. The team behind Flowrite is now focusing on Flow AI, an advanced platform for AI teams to evaluate and improve LLM systems effortlessly. MailMaestro integrates Flowrite's capabilities to enhance email writing experience for users.

Pangea.ai is a leading talent aggregator that helps businesses hire quality technologists by comparing data points for reliable matching. It offers a unified hiring experience in a fragmented market, making it easier to compare and decide among the numerous software development agencies and talent networks available. Pangea.ai's intelligent matching system considers over 100 data points to find the best fit for businesses, while its rigorous vetting process evaluates expertise, client satisfaction, and team health. Businesses can choose to self-serve their way to a hire or opt for Pangea.ai's white-glove matching service.

Vision-LLM-Alignment is a repository focused on implementing alignment training for visual large language models (LLMs), including SFT training, reward model training, and PPO/DPO training. It supports various model architectures and provides datasets for training. The repository also offers benchmark results and installation instructions for users.

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.

Open-Source Evaluation for LLM Applications. `continuous-eval` is an open-source package created for granular and holistic evaluation of GenAI application pipelines. It offers modularized evaluation, a comprehensive metric library covering various LLM use cases, the ability to leverage user feedback in evaluation, and synthetic dataset generation for testing pipelines. Users can define their own metrics by extending the Metric class. The tool allows running evaluation on a pipeline defined with modules and corresponding metrics. Additionally, it provides synthetic data generation capabilities to create user interaction data for evaluation or training purposes.

Rageval is an evaluation tool for Retrieval-augmented Generation (RAG) methods. It helps evaluate RAG systems by performing tasks such as query rewriting, document ranking, information compression, evidence verification, answer generation, and result validation. The tool provides metrics for answer correctness and answer groundedness, along with benchmark results for ASQA and ALCE datasets. Users can install and use Rageval to assess the performance of RAG models in question-answering tasks.

Tonic Validate is a framework for the evaluation of LLM outputs, such as Retrieval Augmented Generation (RAG) pipelines. Validate makes it easy to evaluate, track, and monitor your LLM and RAG applications. Validate allows you to evaluate your LLM outputs through the use of our provided metrics which measure everything from answer correctness to LLM hallucination. Additionally, Validate has an optional UI to visualize your evaluation results for easy tracking and monitoring.

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.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate Language Model Models (LLMs) and LLM applications. It brings Benchmarking and Red-Teaming together to assist AI developers, compliance teams, and AI system owners in assessing LLM performance. Moonshot can be accessed through various interfaces including User-friendly Web UI, Interactive Command Line Interface, and seamless integration into MLOps workflows via Library APIs or Web APIs. It offers features like benchmarking LLMs from popular model providers, running relevant tests, creating custom cookbooks and recipes, and automating Red Teaming to identify vulnerabilities in AI systems.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features such as a Virtual API System with caching and API simulators, a new set of solvable queries determined by LLMs, and a Stable Evaluation System using GPT-4. The Virtual API Server can be set up either by building from source or using a prebuilt Docker image. Users can test the server using provided scripts and evaluate models with Solvable Pass Rate and Solvable Win Rate metrics. The tool also includes model experiments results comparing different models' performance.

PyLLMs is a minimal Python library designed to connect to various Language Model Models (LLMs) such as OpenAI, Anthropic, Google, AI21, Cohere, Aleph Alpha, and HuggingfaceHub. It provides a built-in model performance benchmark for fast prototyping and evaluating different models. Users can easily connect to top LLMs, get completions from multiple models simultaneously, and evaluate models on quality, speed, and cost. The library supports asynchronous completion, streaming from compatible models, and multi-model initialization for testing and comparison. Additionally, it offers features like passing chat history, system messages, counting tokens, and benchmarking models based on quality, speed, and cost.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features like Virtual API System, Solvable Queries, and Stable Evaluation System. The benchmark ensures consistency through a caching system and API simulators, filters queries based on solvability using LLMs, and evaluates model performance using GPT-4 with metrics like Solvable Pass Rate and Solvable Win Rate.

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.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

OSWorld is a benchmarking tool designed to evaluate multimodal agents for open-ended tasks in real computer environments. It provides a platform for running experiments, setting up virtual machines, and interacting with the environment using Python scripts. Users can install the tool on their desktop or server, manage dependencies with Conda, and run benchmark tasks. The tool supports actions like executing commands, checking for specific results, and evaluating agent performance. OSWorld aims to facilitate research in AI by providing a standardized environment for testing and comparing different agent baselines.

A Rust based tool to evaluate LLM models, prompts and model params. It automates the process of selecting the best model parameters, given an LLM model and a prompt, iterating over the possible combinations and letting the user visually inspect the results. The tool assumes the user has Ollama installed and serving endpoints, either in `localhost` or in a remote server. Key features include: * Automatically fetches models from local or remote Ollama servers * Iterates over different models and params to generate inferences * A/B test prompts on different models simultaneously * Allows multiple iterations for each combination of parameters * Makes synchronous inference calls to avoid spamming servers * Optionally outputs inference parameters and response metadata (inference time, tokens and tokens/s) * Refetching of individual inference calls * Model selection can be filtered by name * List experiments which can be downloaded in JSON format * Configurable inference timeout * Custom default parameters and system prompts can be defined in settings

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

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A System Architect Coach guiding you through system design principles and best practices. Explains CAP theorem like no one else

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I review system designs and suggest ideal architectures.

Crea pruebas técnicas para programadores.

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Ethics-focused GPT builder assistant based on European AI guidelines, recommendations and regulations

An expert in Drug Delivery Systems Industry, providing in-depth, accurate insights.

Provides expert guidance in transportation engineering projects.

可以根据所给出的企业合规整改案例，从企业犯罪的内生性结构原因的诊断、制度纠错和专项合规体系构建等三个方面，分析企业合规整改的主要框架，并对合规整改的有效性作出评价。

Advises on sustainable engineering solutions to environmental challenges.

Your Edexcel A level maths assistant. Ask for new questions. Help for the next step in your working out. Even send me a picture of a question and i can tell you what exam it is from.

I will score your Mind Blowing Startup Ideas, helping your to evaluate faster.

I'll help you evaluate your writing to make sure it's engaging, informative, and flows well. Uses principles from "Made to Stick"

The main objective of a personalized ChatGPT for reading laboratory tests is to evaluate laboratory test results and create a spreadsheet with the evaluation results and possible solutions.

As a Search Quality Rater, you will help evaluate search engine quality around the world.

Business Model Canvas Creator - Build and evaluate your business model

Guide to unbiasedly evaluate different job opportunities