Best AI tools for< Rank Agents >

Businessflow AI is a recruitment software powered by AI agents that helps companies find the best-fit applicants at a higher speed and reduced cost. It offers features such as resume analysis, applicant ranking, AI-powered interviews, and a general assistant. Businessflow AI aims to revolutionize the recruitment process by leveraging AI to automate tasks and provide data-driven insights.

Bitscale is an AI tool designed to help growth teams build scalable AI workflows. It empowers growth teams to research prospects, personalize reachouts, and generate A+ content. The tool allows users to research prospects at scale in an intuitive spreadsheet UI, enrich data from 20+ sources, and build outreach campaigns in an Excel-like interface. With features like sales booster, personalized outreach, and utilizing powerful enrichment from Google News and landing pages, Bitscale aims to enhance lead profiles and provide unmatched speed and scalability for marketing challenges. Trusted by fast-growing companies worldwide, Bitscale offers marketing magic by finding topics, generating SEO-optimized content, and helping users rank on Google quickly.

Rank Math is an AI-powered SEO tool that helps you optimize your website for search engines. It offers a variety of features to help you improve your website's ranking, including keyword research, on-page optimization, and link building. Rank Math also provides detailed analytics to help you track your progress and identify areas for improvement.

Rank One Computing (ROC) is an American-made provider of multimodal biometrics and computer vision solutions, specializing in face recognition, fingerprint recognition, and artificial intelligence technologies. Trusted by the U.S. military, law enforcement, and leading FinTech brands, ROC offers top-ranked software for identity proofing and threat detection. Their suite of products includes ROC SDK, ROC Watch, and custom enterprise AI development services. With a focus on security and efficiency, ROC aims to make the world safer and more convenient through unbiased and privacy-conscious applications.

AI Top Rank is an AI tool designed to gather feedback and feature requests from users. It provides a platform for users to share their ideas, suggestions, and feedback on various topics. The tool helps in organizing and prioritizing feedback to improve products or services. With AI capabilities, it offers intelligent insights and analysis to drive decision-making processes. AI Top Rank aims to enhance user engagement and satisfaction by incorporating user feedback into product development.

AlphaRank is an AI SEO optimizer tool designed to boost website traffic by providing advanced SEO solutions. It offers a comprehensive suite of features to audit and optimize websites, leveraging AI algorithms and a vast database of keywords and merchant insights. Trusted by top-tier partners, AlphaRank aims to enhance content relevance, user engagement, and SEO precision for businesses, bloggers, and freelancers. The tool streamlines SEO operations, provides market insights, and offers expert recommendations for technical and content improvements.

Google Business Profile Growth Manager is an application that helps businesses manage their Google Business Profile and improve their local SEO. It offers a variety of features to help businesses save time and grow their online presence, including the ability to manage multiple locations, schedule posts, monitor growth, and get AI-powered insights.

Quattr Inc is the ultimate AI-powered SEO platform designed to help businesses rank better, faster, and at scale. The platform offers a suite of AI tools and features to optimize content, enhance user experience, and improve discoverability. With Quattr, users can automate over 30 manual SEO tasks, receive AI-driven recommendations, and work with a dedicated SEO concierge to drive measurable results. The platform is built to think like a search engine, providing data-driven insights and actionable recommendations for improving SEO performance.

CanIRank is an AI-powered SEO software designed for small businesses and startups to improve their Google rankings. It provides specific action recommendations based on AI analysis, offers DIY instructions or the option to delegate tasks to SEO consultants. The software helps users understand why pages rank where they do, identifies changes for impactful results, and notifies users of new content ideas and ranking changes. CanIRank automates keyword research, provides insights on competitor targeting, and calculates a Keyword ROI Score. It offers SERP analysis, rank tracking, and competitive analysis tools to help users make data-driven decisions and optimize their SEO strategies.

CTRify is an AI-powered SEO action platform that helps businesses create websites that rank on Google. By providing a single keyword to the platform's artificial intelligence, businesses can boost their SERP rankings, organic CTR, dwell time, and pogo sticking. CTRify also provides organic traffic from millions of real desktop and mobile devices connected from residential IPs of top mobile carriers from all locations of the world.

SEOByAI is a website that offers a suite of free AI-powered SEO tools to help businesses improve their search engine rankings. The tools include an AI blog featured image generator, an AI content detector, an AI outline generator, an AI title generator, an AI meta description generator, an AI SEO topic cluster generator, an AI paragraph generator, and an AI paragraph rewriter. The website also features a blog with articles on SEO best practices and a newsletter that provides updates on the latest SEO trends.

FluidSEO is an AI-infused Webflow SEO application that helps users fix SEO problems efficiently. It offers features such as smart alt text generation, schema creation, bulk updates, and smart descriptions. The application streamlines the process of adding metadata and ensuring alt text for images, saving users time and effort. With FluidSEO, users can implement best practice SEO in Webflow with confidence, improve their site's ranking on Google, and simplify on-page SEO tasks. The application is designed to be user-friendly, making it suitable for Webflow designers, SEO managers, content marketers, and beginners.

Autoblogging.ai is an AI-powered article writer that helps users generate high-quality, SEO-optimized content in one click. It offers multiple modes, including Quick Mode for fast article generation, Pro Mode for customization, and Godlike Mode for keyword-rich content. Autoblogging.ai supports multiple languages and provides features like bulk generation, automatic WordPress posting, and Amazon review generation. It is designed to save time and improve online visibility for bloggers, website owners, and agencies.

Outranking is an AI-powered SEO content writing and optimization tool that helps users create high-quality, SEO-friendly content with ease. It leverages cutting-edge technologies like Google NLP and OpenAI GPT-4 to provide features such as AI-assisted writing, keyword clustering, content briefs, and automatic optimization. Outranking streamlines the content creation process, from generating SEO outlines to producing first drafts, optimizing content, and managing workflows. Trusted by top companies worldwide, Outranking offers a data-backed solution for achieving predictable ranking success and increasing website traffic. With a focus on user experience and efficiency, Outranking is designed to help users create content that ranks and resonates with their target audience.

Outranking is an AI-powered SEO content writing and optimization tool that helps businesses create high-quality, search engine-friendly content. It offers a range of features to help users research, plan, write, and optimize their content, including an AI-powered writing assistant, keyword research and analysis tools, and on-page optimization suggestions. Outranking is designed to help businesses improve their search engine rankings and drive more traffic to their websites.

Emplibot is an AI-powered tool designed for automated blogging on WordPress. It helps users to publish articles on their blog and share them on social media in a fully automated manner. The tool offers features such as automated keyword research, AI-generated images, in-content infographics, internal and external linking, and auto-publishing on social media platforms. Emplibot aims to simplify content creation and distribution for businesses, ultimately boosting their SEO performance and online visibility.

LinkActions is a fully-automated internal linking tool that helps you build internal links on your website to improve your SEO, increase organic traffic, and boost sales. It analyzes your website's content and automatically creates and inserts internal links onto your website. LinkActions works with any CMS and is optimized for websites with hundreds to thousands of pages and long-form content over 500 words per page.

Search Alkemy is a free AI-powered SEO keyword research and topic clustering tool that helps content marketers and SEOs discover high-performing keywords, analyze search intent, and create content that ranks. With Search Alkemy, you can:

RankBot is an AI-driven SEO tool that revolutionizes the way websites optimize their search engine rankings. By leveraging artificial intelligence, RankBot automates the process of building backlinks and enhancing on-page SEO, eliminating the need for manual labor and extensive keyword research. With personalized strategies and effortless SEO mastery, RankBot empowers users to outsmart competitors and achieve top search engine rankings with minimal effort. The tool provides simple reporting, tracks keyword performance, and offers a user-friendly interface for seamless optimization. Despite its confidence, RankBot aims to complement traditional SEO agencies rather than replace them, offering a cost-effective and efficient solution for website optimization.

YACSS is an AI website generator and Automated Cloud Stacking Software that offers advanced SEO solutions for building websites, generating backlinks, and boosting domain authority. It provides features like automated website creation, cloud-based backlinking, topic clusters, local SEO optimization, and AI content generation. YACSS is designed to streamline the web design process, improve online presence, and enhance Google rankings through innovative technology and automation.

RAGElo is a streamlined toolkit for evaluating Retrieval Augmented Generation (RAG)-powered Large Language Models (LLMs) question answering agents using the Elo rating system. It simplifies the process of comparing different outputs from multiple prompt and pipeline variations to a 'gold standard' by allowing a powerful LLM to judge between pairs of answers and questions. RAGElo conducts tournament-style Elo ranking of LLM outputs, providing insights into the effectiveness of different settings.

LABO is a time series forecasting and analysis framework that integrates pre-trained and fine-tuned LLMs with multi-domain agent-based systems. It allows users to create and tune agents easily for various scenarios, such as stock market trend prediction and web public opinion analysis. LABO requires a specific runtime environment setup, including system requirements, Python environment, dependency installations, and configurations. Users can fine-tune their own models using LABO's Low-Rank Adaptation (LoRA) for computational efficiency and continuous model updates. Additionally, LABO provides a Python library for building model training pipelines and customizing agents for specific tasks.

Odyssey is a framework designed to empower agents with open-world skills in Minecraft. It provides an interactive agent with a skill library, a fine-tuned LLaMA-3 model, and an open-world benchmark for evaluating agent capabilities. The framework enables agents to explore diverse gameplay opportunities in the vast Minecraft world by offering primitive and compositional skills, extensive training data, and various long-term planning tasks. Odyssey aims to advance research on autonomous agent solutions by providing datasets, model weights, and code for public use.

`npcsh` is a python-based command-line tool designed to integrate Large Language Models (LLMs) and Agents into one's daily workflow by making them available and easily configurable through the command line shell. It leverages the power of LLMs to understand natural language commands and questions, execute tasks, answer queries, and provide relevant information from local files and the web. Users can also build their own tools and call them like macros from the shell. `npcsh` allows users to take advantage of agents (i.e. NPCs) through a managed system, tailoring NPCs to specific tasks and workflows. The tool is extensible with Python, providing useful functions for interacting with LLMs, including explicit coverage for popular providers like ollama, anthropic, openai, gemini, deepseek, and openai-like providers. Users can set up a flask server to expose their NPC team for use as a backend service, run SQL models defined in their project, execute assembly lines, and verify the integrity of their NPC team's interrelations. Users can execute bash commands directly, use favorite command-line tools like VIM, Emacs, ipython, sqlite3, git, pipe the output of these commands to LLMs, or pass LLM results to bash commands.

ScreenAgent is a project focused on creating an environment for Visual Language Model agents (VLM Agent) to interact with real computer screens. The project includes designing an automatic control process for agents to interact with the environment and complete multi-step tasks. It also involves building the ScreenAgent dataset, which collects screenshots and action sequences for various daily computer tasks. The project provides a controller client code, configuration files, and model training code to enable users to control a desktop with a large model.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

LLM4IR-Survey is a collection of papers related to large language models for information retrieval, organized according to the survey paper 'Large Language Models for Information Retrieval: A Survey'. It covers various aspects such as query rewriting, retrievers, rerankers, readers, search agents, and more, providing insights into the integration of large language models with information retrieval systems.

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

llm-rankers is a repository that provides implementations for Pointwise, Listwise, Pairwise, and Setwise Document Ranking using Large Language Models. It includes various methods for reranking documents retrieved by a first-stage retriever, such as BM25. The repository offers examples and code snippets for using LLMs to improve document ranking performance in information retrieval tasks. Additionally, it introduces a new setwise reranker called Rank-R1 with reasoning ability.

LLM-as-a-Judge is a repository that includes papers discussed in a survey paper titled 'A Survey on LLM-as-a-Judge'. The repository covers various aspects of using Large Language Models (LLMs) as judges for tasks such as evaluation, reasoning, and decision-making. It provides insights into evaluation pipelines, improvement strategies, and specific tasks related to LLMs. The papers included in the repository explore different methodologies, applications, and future research directions for leveraging LLMs as evaluators in various domains.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

OpenRedTeaming is a repository focused on red teaming for generative models, specifically large language models (LLMs). The repository provides a comprehensive survey on potential attacks on GenAI and robust safeguards. It covers attack strategies, evaluation metrics, benchmarks, and defensive approaches. The repository also implements over 30 auto red teaming methods. It includes surveys, taxonomies, attack strategies, and risks related to LLMs. The goal is to understand vulnerabilities and develop defenses against adversarial attacks on large language models.

This repository focuses on Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). It provides code and resources to augment LLMs with real-time data for dynamic, context-aware applications. The content covers topics such as semantic search, fine-tuning embeddings, building RAG chatbots, evaluating LLMs, and using knowledge graphs in RAG. Prerequisites include Python skills, knowledge of machine learning and LLMs, and introductory experience with NLP and AI models.

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