Best AI tools for< Multi-agent Collaboration >

Mentals.ai is an operating system for AI agents that enables users to design and deploy complex AI agents using natural language instructions. It focuses on creativity and logic rather than programming, allowing for multi-agent collaboration, advanced features like memory and code execution, and various use cases such as business automation, personal automation, and marketing automation. The platform also supports the creation of intelligent chatbots, virtual employees, and multi-agent systems, revolutionizing productivity and problem-solving in various domains.

SuperAGI is a leading research organization focused on Generalized Super Intelligence. They work on research in technical areas such as Neurosymbolic AI, Autonomous Agents & Multi-Agent Systems, New Model Architectures, System 2 Thinking, Recursive Self-Improving Systems, and other socio-economic super AGI-related topics such as Digital Workforce, Algorithmic Governance, UBI, etc.

GPT Assistant is an advanced AI chatbot designed for seamless conversations and helpful assistance. It offers fast and authentic AI responses, advanced natural language processing, and intelligent assistance with PDFs. The application integrates directly into Discord, providing users with convenient access to its powerful AI capabilities. Users can maximize productivity, streamline workflows, and engage in interactive and collaborative conversations effortlessly. GPT Assistant simplifies tasks such as summarizing PDF documents, enhancing coding experiences, and fostering community interactions through AI integration.

ClearFeed is an AI-powered support platform designed for Slack and MS Teams, offering a next-gen support experience. It streamlines communication, enables private collaboration, and delivers resolutions 5X faster. The platform brings core helpdesk functions to Slack and MS Teams, leveraging AI to resolve queries efficiently. ClearFeed is trusted by leading companies globally and has received positive reviews for its ability to enhance support efficiency and productivity.

DOO is an AI-powered customer experience platform that helps businesses automate interactions, personalize engagement, and scale customer service effortlessly across all channels. It seamlessly connects, customizes, and optimizes every interaction, bringing all customer conversations into one place. With features like automated responses, unified inbox, multi-channel integration, control tower, and analytics hub, DOO empowers businesses to elevate customer experience and optimize customer satisfaction. The platform enables quick, personalized responses, centralizes conversations, enhances team productivity, provides data insights, and offers personalized engagement. DOO is designed to transform customer experience through AI technology, offering significant growth, efficiency, and revenue benefits.

AskJimmy is a platform for AI agents focused on finance and trading. It offers exposure to a diverse range of strategies managed by top-notch AI Agents. The platform allows users to compose autonomous agents and trading strategies with extreme customization. It aims to create a decentralized multi-strategy collaborative hedge-fund powered by AI agents. AskJimmy is designed to aggregate non-correlated autonomous agent strategies into a diversified subnet, shaping the future of multi-strategies decentralized hedge-fund.

GAIA is a powerful creation engine designed for the AI Age. It provides users with advanced tools and capabilities to develop AI applications, machine learning models, and data analytics solutions. With a user-friendly interface and robust features, GAIA empowers individuals and organizations to harness the potential of artificial intelligence for various projects and initiatives. Whether you are a data scientist, developer, or AI enthusiast, GAIA offers a comprehensive platform to bring your ideas to life and drive innovation in the rapidly evolving AI landscape.

DataSpark AI Multi-Agent Platform is an advanced artificial intelligence tool developed by DataSpark, Inc. The platform leverages cutting-edge AI technology to provide users with a powerful solution for multi-agent systems. With DataSpark AI, users can access the first GenAI Super Agent, enabling them to discover new insights and make informed decisions. The platform is designed to streamline complex processes and enhance productivity across various industries.

Salieri is a multi-agent LLM home multiverse platform that offers an efficient, trustworthy, and automated AI workflow. The innovative Multiverse Factory allows developers to elevate their projects by generating personalized AI applications through an intuitive interface. The platform aims to optimize user queries via LLM API calls, reduce expenses, and enhance the cognitive functions of AI agents. Salieri's team comprises experts from top AI institutes like MIT and Google, focusing on generative AI, neural knowledge graph, and composite AI models.

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 and safety-first approach. The platform offers user-friendly dashboards, visual reports, smart keyword generators, content evaluation, SEO goal setting, automated alerts, actionable SEO tips, and link optimization wizards. Users can dispatch tasks to AI agents in groups and take action on tasks automatically through decentralized multi-agent orchestration. Questflow also facilitates the distribution of economic incentives to creators and guardians of AI agents via a blockchain network, rewarding them for their contributions to the future of work.

Questflow is a decentralized AI agent economy platform that allows 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.

GenWorlds is an event-based communication framework for building multi-agent systems. It offers a platform for creating Generative AI applications where users can design customizable environments, utilize scalable architecture, access a repository of memories and tools, choose cognitive processes for agents, and pick coordination protocols. GenWorlds aims to foster a vibrant community of developers, AI enthusiasts, and innovators to collaborate, innovate, share knowledge, and grow together.

GoodGist is an Agentic AI platform for Business Process Automation that goes beyond traditional RPA tools by offering Adaptive Multi-Agent AI with Human-in-the-loop workflows. It enables end-to-end process automation, supports unstructured and multimodal data, ensures real-time decision-making, and maintains human oversight for scalable performance. GoodGist caters to various industries like manufacturing, supply chain, banking, insurance, healthcare, retail, and CPG, providing enterprise-grade security, compliance, and rapid ROI.

Integrail is an AI tool that simplifies the process of building AI applications by allowing users to design and deploy multi-agent applications without the need for coding skills. It offers a range of features such as integrating external apps, optimizing cost and accuracy, and deploying applications securely in the cloud or on-premises. Integrail Studio provides access to popular AI models and enables users to transform business workflows efficiently.

AgentForge is a powerful AI application that simplifies the creation and customization of AI agents. It offers a comprehensive toolkit with pre-built agents, customizable graphs, and reusable UI components. The platform allows users to effortlessly build and customize AI agents, reducing the complexity and cost associated with developing AI solutions from scratch. With seamless integration with popular AI tools and platforms, AgentForge empowers businesses to unlock the full potential of AI technology.

Libromi Connect is an AI-powered WhatsApp cloud business platform that offers advanced features to streamline customer engagement and automate interactions. It provides a no-code chatbot builder, native eCommerce integration within WhatsApp, bulk messaging capabilities, and a GPT4 AI chatbot. The platform also includes a team inbox for multi-agent chat support and CRM features for sales and support chat. Libromi Connect aims to revolutionize online shopping and customer service by leveraging the power of AI and WhatsApp's popularity.

crewAI is a platform for Multi AI Agents Systems that offers a user-friendly framework for automating workflows with AI agents. It simplifies the process of building and deploying multi-agent automations, providing support for various AI models and templates. With a focus on privacy and security, crewAI ensures that each agent runs in isolated environments. The platform is suitable for enterprises and developers looking to leverage AI technologies effectively.

AIAgent.app is a web application that utilizes artificial intelligence to automate tasks and decision-making processes based on user-defined goals. It employs a multi-agent system, where each agent focuses on specific tasks such as execution, task creation, prioritization, and iteration. By leveraging the power of GPT-4, AIAgent.app democratizes access to cutting-edge AI technology, enabling users to enhance their productivity and streamline their workflows.

Langflow is a low-code app builder for RAG and multi-agent AI applications. It is Python-based and agnostic to any model, API, or database. Langflow offers a visual IDE for building and testing workflows, multi-agent orchestration, free cloud service, observability features, and ecosystem integrations. Users can customize workflows using Python and publish them as APIs or export as Python applications.

MindPal is a sophisticated AI tool designed to help professionals automate their tasks and workflows using AI agents and multi-agent workflows. It offers a wide range of features and templates to streamline processes and boost productivity. With MindPal, users can create, customize, and deploy AI-powered solutions for various industries and tasks, saving time and enhancing efficiency. The platform is recommended by innovative professionals worldwide for its effectiveness in simplifying complex tasks and generating valuable insights.

MetaAgent is a multi-agent collaboration platform designed to build, manage, and deploy multi-modal AI agents without the need for coding. Users can easily create AI agents by editing a yml file or using the provided UI. The platform supports features such as building LLM-based AI agents, multi-modal interactions with users using texts, audios, images, and videos, creating a company of agents for complex tasks like drawing comics, vector database and knowledge embeddings, and upcoming features like UI for creating and using AI agents, fine-tuning, and RLHF. The tool simplifies the process of creating and deploying AI agents for various tasks.

agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on multi-agent collaborative patterns, integrating domain experience to help agents solve problems in various fields. The framework includes pattern components like PEER and DOE for event interpretation, industry analysis, and financial report generation. It offers features for agent construction, multi-agent collaboration, and domain expertise integration, aiming to create intelligent applications with professional know-how.

CEO is an intuitive and modular AI agent framework designed for task automation. It provides a flexible environment for building agents with specific abilities and personalities, allowing users to assign tasks and interact with the agents to automate various processes. The framework supports multi-agent collaboration scenarios and offers functionalities like instantiating agents, granting abilities, assigning queries, and executing tasks. Users can customize agent personalities and define specific abilities using decorators, making it easy to create complex automation workflows.

CEO-Agentic-AI-Framework is an ultra-lightweight Agentic AI framework based on the ReAct paradigm. It supports mainstream LLMs and is stronger than Swarm. The framework allows users to build their own agents, assign tasks, and interact with them through a set of predefined abilities. Users can customize agent personalities, grant and deprive abilities, and assign queries for specific tasks. CEO also supports multi-agent collaboration scenarios, where different agents with distinct capabilities can work together to achieve complex tasks. The framework provides a quick start guide, examples, and detailed documentation for seamless integration into research projects.

This repository, named Awesome-Embodied-Agent-with-LLMs, is a curated list of research related to Embodied AI or agents with Large Language Models. It includes various papers, surveys, and projects focusing on topics such as self-evolving agents, advanced agent applications, LLMs with RL or world models, planning and manipulation, multi-agent learning and coordination, vision and language navigation, detection, 3D grounding, interactive embodied learning, rearrangement, benchmarks, simulators, and more. The repository provides a comprehensive collection of resources for individuals interested in exploring the intersection of embodied agents and large language models.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

Praison AI is a low-code, centralised framework that simplifies the creation and orchestration of multi-agent systems for various LLM applications. It emphasizes ease of use, customization, and human-agent interaction. The tool leverages AutoGen and CrewAI frameworks to facilitate the development of AI-generated scripts and movie concepts. Users can easily create, run, test, and deploy agents for scriptwriting and movie concept development. Praison AI also provides options for full automatic mode and integration with OpenAI models for enhanced AI capabilities.

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.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

Daydreams is a generative agent library designed for playing onchain games by injecting context. It is chain agnostic and allows users to perform onchain tasks, including playing any onchain game. The tool is lightweight and powerful, enabling users to define game context, register actions, set goals, monitor progress, and integrate with external agents. Daydreams aims to be 'lite' and 'composable', dynamically generating code needed to play games. It is currently in pre-alpha stage, seeking feedback and collaboration for further development.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

Awesome-AI-Agents is a curated list of projects, frameworks, benchmarks, platforms, and related resources focused on autonomous AI agents powered by Large Language Models (LLMs). The repository showcases a wide range of applications, multi-agent task solver projects, agent society simulations, and advanced components for building and customizing AI agents. It also includes frameworks for orchestrating role-playing, evaluating LLM-as-Agent performance, and connecting LLMs with real-world applications through platforms and APIs. Additionally, the repository features surveys, paper lists, and blogs related to LLM-based autonomous agents, making it a valuable resource for researchers, developers, and enthusiasts in the field of AI.

This repository provides a comprehensive survey of research papers on large language model (LLM)-based game agents. LLMs are powerful AI models that can understand and generate human language, and they have shown great promise for developing intelligent game agents. This survey covers a wide range of topics, including adventure games, crafting and exploration games, simulation games, competition games, cooperation games, communication games, and action games. For each topic, the survey provides an overview of the state-of-the-art research, as well as a discussion of the challenges and opportunities for future work.

Floki is an open-source framework for researchers and developers to experiment with LLM-based autonomous agents. It provides tools to create, orchestrate, and manage agents while seamlessly connecting to LLM inference APIs. Built on Dapr, Floki leverages a unified programming model that simplifies microservices and supports both deterministic workflows and event-driven interactions. By bringing together these features, Floki provides a powerful way to explore agentic workflows and the components that enable multi-agent systems to collaborate and scale, all powered by Dapr.

LLM Agents Papers is a repository containing must-read papers on Large Language Model Agents. It covers a wide range of topics related to language model agents, including interactive natural language processing, large language model-based autonomous agents, personality traits in large language models, memory enhancements, planning capabilities, tool use, multi-agent communication, and more. The repository also provides resources such as benchmarks, types of tools, and a tool list for building and evaluating language model agents. Contributors are encouraged to add important works to the repository.

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.

This repository maintains a list of research papers on LLM-based Multi-Agents, categorized into five main streams: Multi-Agents Framework, Multi-Agents Orchestration and Efficiency, Multi-Agents for Problem Solving, Multi-Agents for World Simulation, and Multi-Agents Datasets and Benchmarks. The repository also includes a survey paper on LLM-based Multi-Agents and a table summarizing the key findings of the survey.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

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