Best AI tools for< Perform Evaluations >

functime is a time-series machine learning tool designed to perform forecasting at scale. It provides a comprehensive set of functions and resources to assist users in analyzing and evaluating time-series data. With features like scoring, ranking, and plotting functions, functime aims to simplify the process of forecasting and make it accessible to users of all levels of expertise. The tool also offers an API reference for developers looking to integrate time-series forecasting capabilities into their applications.

AdGen AI is an AI-powered creative generator that helps businesses create high-performing ad copy and visuals for multiple ad channels. It uses machine learning models to analyze product data and generate a variety of ad creatives that are tailored to the target audience. AdGen AI also allows users to publish ads directly from the platform, making it easy to launch and manage ad campaigns.

JobInterview.guru is an AI-powered platform designed to provide personalized interview training for job seekers. Leveraging advanced AI technology, the platform offers realistic job interview simulations, detailed insights into interview questions, and personalized feedback to help users prepare effectively. With a focus on efficiency and cost-effectiveness, JobInterview.guru aims to empower users to confidently navigate their job interviews and land their dream jobs.

LambdaTest is a next-generation mobile apps and cross-browser testing cloud platform that offers a wide range of testing services. It allows users to perform manual live-interactive cross-browser testing, run Selenium, Cypress, Playwright scripts on cloud-based infrastructure, and execute AI-powered automation testing. The platform also provides accessibility testing, real devices cloud, visual regression cloud, and AI-powered test analytics. LambdaTest is trusted by over 2 million users globally and offers a unified digital experience testing cloud to accelerate go-to-market strategies.

Laxis is a revolutionary AI Meeting Assistant designed to capture and distill key insights from every customer interaction effortlessly. It seamlessly integrates across platforms, from online meetings to CRM updates, all with a user-friendly interface. Laxis empowers revenue teams to maximize every customer conversation, ensuring no valuable detail is missed. With Laxis, sales teams can close more deals with AI note-taking and insights from client conversations, business development teams can engage prospects more effectively and grow their business faster, marketing teams can repurpose podcasts, webinars, and meetings into engaging content with a single click, product and market researchers can conduct better research interviews that get to the "aha!" moment faster, project managers can remember key takeaways and status updates, and capture them for progress reports, and product and UX designers can capture and organize insights from their interviews and user research.

CampaignBuilder.AI is an AI-powered platform that enables users to quickly generate and launch AI-optimized advertising campaigns across major ad platforms. The tool offers features such as AI-generated copywriting, audience targeting, creative building, and campaign exporting. It provides creative freedom and full-funnel capabilities, making campaign creation efficient and effective for businesses of all sizes. With CampaignBuilder.AI, users can save time, improve campaign performance, and scale their advertising efforts with ease.

Laxis is an AI Meeting Assistant designed to empower revenue teams by capturing and distilling key insights from customer interactions effortlessly. It offers seamless integration across platforms, from online meetings to CRM updates, with a user-friendly interface. Laxis helps users stay focused during meetings, auto-generate meeting summaries, identify customer requirements, and extract valuable insights. It supports multilingual interactions, real-time transcriptions, and provides answers based on past conversations. Trusted by over 35,000 business professionals from 3000 organizations, Laxis saves time, improves note-taking, and enhances communication with clients and prospects.

Ask Blue J is a generative AI tool designed specifically for tax experts. It provides fast, verifiable answers to complex tax questions, helping professionals work smarter and more efficiently. With its extensive database of curated tax content and industry-leading AI technology, Ask Blue J enables users to conduct efficient research, expedite drafting, and enhance their overall productivity.

Blue J is a legal technology company founded in 2015, dedicated to enhancing tax research with the power of AI. Their AI-powered tool, Ask Blue J, provides fast and verifiable answers to tax questions, enabling tax professionals to work more efficiently. Blue J's generative AI technology helps users find authoritative sources quickly, expedite drafting processes, and cater to junior staff's research needs. The tool is trusted by hundreds of leading firms and offers a comprehensive database of curated tax content.

Sales Closer AI is an AI-powered sales tool designed to help businesses scale their sales operations by creating AI agents capable of handling various tasks such as phone calls, scheduling, and conducting personalized discovery calls. The tool integrates seamlessly with existing CRM and marketing tools, enabling users to uncover customer pain points, build rapport, and deliver interactive demos in multiple languages. Sales Closer AI continuously learns and optimizes its approach, providing detailed notes for future reference and boosting conversion rates across different industries.

GPTConsole is an AI-powered platform that helps developers build production-ready applications faster and more efficiently. Its AI agents can generate code for a variety of applications, including web applications, AI applications, and landing pages. GPTConsole also offers a range of features to help developers build and maintain their applications, including an AI agent that can learn your entire codebase and answer your questions, and a CLI tool for accessing agents directly from the command line.

Remy is an AI-powered platform designed to help product security and compliance teams resolve security risks early. It offers a scalable design review solution that automates the identification and triage of high-impact engineering proposals, providing full visibility and reducing cost, risk, and time associated with security design reviews. Remy streamlines review processes, generates AI-based questions, and offers clear metrics and audit trails to enhance security practices. The platform is enterprise-ready, offering SSO for convenient logins, scalability, and customization to meet diverse enterprise needs.

Validator by Yazero is a platform that helps users validate their startup ideas using AI. It provides a community where users can share their ideas, get feedback, and find collaborators. Validator also offers a variety of features to help users improve their ideas, such as idea validation, market research, and financial planning.

pdfAssistant is a powerful AI chatbot designed to assist users with various PDF processing tasks. It offers a user-friendly chat-based interface that allows users to convert, watermark, merge, split, and perform other PDF-related operations using natural language commands. The application is powered by industry-leading PDF and AI technology, providing fast and accurate results. With pdfAssistant, users can work smarter and more efficiently by simplifying complex PDF software processes.

KYP.ai is a productivity intelligence platform that offers a 360° view of organizations across people, process, and technology dimensions. It provides instant productivity intelligence, end-to-end process optimization, holistic productivity insights, ROI-driven automation, and unparalleled scalability. The platform helps in live visibility, immediate impact, hybrid workplace management, technology landscape rationalization, and AI-powered aggregation and analysis. KYP.ai focuses on workforce enablement, no integration hassles, no-code configuration, and secure, privacy-compliant data processing.

Solidroad is an AI-first training and feedback platform that turns company knowledge-base into immersive training programs. It offers personalized coaching, realistic simulations, and real-time feedback to improve team performance. The platform aims to make training programs easier to manage and more engaging for employees.

Vizly is an AI-powered data analysis tool that empowers users to make the most of their data. It allows users to chat with their data, visualize insights, and perform complex analysis. Vizly supports various file formats like CSV, Excel, and JSON, making it versatile for different data sources. The tool is free to use for up to 10 messages per month and offers a student discount of 50%. Vizly is suitable for individuals, students, academics, and organizations looking to gain actionable insights from their data.

Yogger is a video analysis app and AI movement screening tool that enables users to analyze movement anytime, anywhere. The technology allows for motion capture on mobile devices, making it easy to improve performance, prevent injuries, and achieve personal bests effortlessly. With Yogger, users can perform multiple movements, gather information instantly, and receive detailed reports on movement screenings. It is a motivational tool for clients looking to improve their assessment scores and a convenient way for trainers and coaches to assess clients and communicate ways to enhance performance.

GeekSight Inc. offers a range of Trello Power-Ups designed to enhance team collaboration and productivity. One of their key products is Notes & Docs, an AI-powered note-taking tool integrated with Trello. The tool aims to streamline task management by providing comprehensive task context information organization and content creation workflows. Additionally, they provide PersonaTool for building customer personas and Card Annotations for enhancing communication on Trello boards.

Dreamwriter is an AI-powered content creation tool that allows users to design beautiful, on-brand premium content in minutes. By leveraging the power of AI and the user's brand voice, Dreamwriter helps in developing hard-hitting PDFs & PPTs tailored to the exact target audience. The tool features an intuitive UI editor, real-time collaboration, simplified daily content generation, and the ability to write in multiple languages. Dreamwriter aims to streamline the content creation process by providing a toolbox of leading solutions to produce premium content at unprecedented speeds.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

UHGEval is a comprehensive framework designed for evaluating the hallucination phenomena. It includes UHGEval, a framework for evaluating hallucination, XinhuaHallucinations dataset, and UHGEval-dataset pipeline for creating XinhuaHallucinations. The framework offers flexibility and extensibility for evaluating common hallucination tasks, supporting various models and datasets. Researchers can use the open-source pipeline to create customized datasets. Supported tasks include QA, dialogue, summarization, and multi-choice tasks.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

ARTKIT is a Python framework developed by BCG X for automating prompt-based testing and evaluation of Gen AI applications. It allows users to develop automated end-to-end testing and evaluation pipelines for Gen AI systems, supporting multi-turn conversations and various testing scenarios like Q&A accuracy, brand values, equitability, safety, and security. The framework provides a simple API, asynchronous processing, caching, model agnostic support, end-to-end pipelines, multi-turn conversations, robust data flows, and visualizations. ARTKIT is designed for customization by data scientists and engineers to enhance human-in-the-loop testing and evaluation, emphasizing the importance of tailored testing for each Gen AI use case.

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured evaluations (covering language, code, embedding use cases), perform root cause analysis on failure cases and give insights on how to resolve them.

Vivaria is a web application tool designed for running evaluations and conducting agent elicitation research. Users can interact with Vivaria using a web UI and a command-line interface. It allows users to start task environments based on METR Task Standard definitions, run AI agents, perform agent elicitation research, view API requests and responses, add tags and comments to runs, store results in a PostgreSQL database, sync data to Airtable, test prompts against LLMs, and authenticate using Auth0.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

Do-Not-Answer is an open-source dataset curated to evaluate Large Language Models' safety mechanisms at a low cost. It consists of prompts to which responsible language models do not answer. The dataset includes human annotations and model-based evaluation using a fine-tuned BERT-like evaluator. The dataset covers 61 specific harms and collects 939 instructions across five risk areas and 12 harm types. Response assessment is done for six models, categorizing responses into harmfulness and action categories. Both human and automatic evaluations show the safety of models across different risk areas. The dataset also includes a Chinese version with 1,014 questions for evaluating Chinese LLMs' risk perception and sensitivity to specific words and phrases.

Simplifine is an open-source library designed for easy LLM finetuning, enabling users to perform tasks such as supervised fine tuning, question-answer finetuning, contrastive loss for embedding tasks, multi-label classification finetuning, and more. It provides features like WandB logging, in-built evaluation tools, automated finetuning parameters, and state-of-the-art optimization techniques. The library offers bug fixes, new features, and documentation updates in its latest version. Users can install Simplifine via pip or directly from GitHub. The project welcomes contributors and provides comprehensive documentation and support for users.

MMMU is a benchmark designed to evaluate multimodal models on college-level subject knowledge tasks, covering 30 subjects and 183 subfields with 11.5K questions. It focuses on advanced perception and reasoning with domain-specific knowledge, challenging models to perform tasks akin to those faced by experts. The evaluation of various models highlights substantial challenges, with room for improvement to stimulate the community towards expert artificial general intelligence (AGI).

Q-Bench is a benchmark for general-purpose foundation models on low-level vision, focusing on multi-modality LLMs performance. It includes three realms for low-level vision: perception, description, and assessment. The benchmark datasets LLVisionQA and LLDescribe are collected for perception and description tasks, with open submission-based evaluation. An abstract evaluation code is provided for assessment using public datasets. The tool can be used with the datasets API for single images and image pairs, allowing for automatic download and usage. Various tasks and evaluations are available for testing MLLMs on low-level vision tasks.

The 'Awesome LLMs Planning Reasoning' repository is a curated collection focusing on exploring the capabilities of Large Language Models (LLMs) in planning and reasoning tasks. It includes research papers, code repositories, and benchmarks that delve into innovative techniques, reasoning limitations, and standardized evaluations related to LLMs' performance in complex cognitive tasks. The repository serves as a comprehensive resource for researchers, developers, and enthusiasts interested in understanding the advancements and challenges in leveraging LLMs for planning and reasoning in real-world scenarios.

Winter is a UCI chess engine that has competed at top invite-only computer chess events. It is the top-rated chess engine from Switzerland and has a level of play that is super human but below the state of the art reached by large, distributed, and resource-intensive open-source projects like Stockfish and Leela Chess Zero. Winter has relied on many machine learning algorithms and techniques over the course of its development, including certain clustering methods not used in any other chess programs, such as Gaussian Mixture Models and Soft K-Means. As of Winter 0.6.2, the evaluation function relies on a small neural network for more precise evaluations.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

Black Marlin is a UCI compliant chess engine fully written in Rust by Doruk Sekercioglu. It supports Chess960 and features a variety of search algorithms, pruning techniques, and evaluation methods. Black Marlin is designed to be efficient and accurate, and it has been shown to perform well against other top chess engines.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

Azure OpenAI demos is a repository showcasing various demos and use cases of Azure OpenAI services. It includes demos for tasks such as image comparisons, car damage copilot, video to checklist generation, automatic data visualization, text analytics, and more. The repository provides a wide range of examples on how to leverage Azure OpenAI for different applications and industries.

ALMA (Advanced Language Model-based Translator) is a many-to-many LLM-based translation model that utilizes a two-step fine-tuning process on monolingual and parallel data to achieve strong translation performance. ALMA-R builds upon ALMA models with LoRA fine-tuning and Contrastive Preference Optimization (CPO) for even better performance, surpassing GPT-4 and WMT winners. The repository provides ALMA and ALMA-R models, datasets, environment setup, evaluation scripts, training guides, and data information for users to leverage these models for translation tasks.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

Analyzing VC projects and due diligence.

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