Best AI tools for< Conduct Agent-driven Research >

Medallia is an experience management software platform that helps businesses transform customer and employee experiences. It offers a comprehensive feedback capture, role-based reporting, AI & analytics, integrations, and enterprise-grade security. The platform enables end-to-end customer experience management, digital experience tracking, employee listening, agent coaching, and market research solutions across various industries. Medallia also provides resources, training, and support to enhance user experience and drive business growth.

Growth Makers is an AI-powered marketing team that helps businesses grow through growth hacking and marketing strategies. The AI assistants are trained to find clever ways to achieve explosive growth quickly. They perform in-depth research on your target audience, market, USP, UVP, keywords, landing page, pricing, and more to craft winning marketing strategies. Growth Makers can also create blogs and social media content, build a consistent content calendar, conduct competitive keyword research, analyze audience response to refine content strategies, identify hidden growth channels, and make data-driven decisions based on Google Analytics metrics.

Sapia.ai is an AI hiring agent that revolutionizes the recruitment process by conducting structured interviews with candidates, evaluating real skills, and providing valuable insights at scale. Trusted by leading brands, Sapia.ai streamlines hiring processes, enhances candidate experience, and improves hiring outcomes through AI-driven solutions. The platform offers features such as chat and video interviews, interview scheduling, talent insights, and candidate engagement tools. With a focus on speed, fairness, and diversity, Sapia.ai helps organizations find the right talent efficiently and effectively.

HeyMilo AI is a generative AI-powered voice agent application designed to help companies and recruiting agencies scale their interview processes. It offers AI-powered voice agents capable of conducting two-way conversational interviews, providing real-time candidate insights, and seamless integration with existing recruiting tools. HeyMilo aims to make interviewing easier, faster, and more effective by creating and sharing agents, inviting candidates for interviews, and analyzing interviews to provide comprehensive candidate reports.

Connex AI is an advanced AI platform offering a wide range of AI solutions for businesses across various industries. The platform provides cutting-edge features such as AI Agent, AI Guru, AI Voice, AI Analytics, Real-Time Coaching, Automated Speech Recognition, Sentiment Analysis, Keyphrase Analysis, Entity Recognition, LLM Topic-Based Modelling, SMS Live Chat, WhatsApp Voice, Email Dialler, PCI DSS, Social Media Flow, Calendar Schedular, Staff Management, Gamify Shop, PDF Builder, Pricing Matrix, Themes, Article Builder, Marketplace Integrations, and more. Connex AI aims to enhance customer engagement, workforce productivity, sales, and customer satisfaction through its innovative AI-driven solutions.

PrimeLSA is an AI-driven Google Local Services Ads management agency that specializes in boosting local visibility for small and medium-sized businesses. They offer expert management services for various industries, including plumbing, HVAC, electrical, law, and more. PrimeLSA conducts comprehensive analyses of Local Services Ads accounts, identifies gaps, and implements tailored strategies to optimize campaigns for increased visibility and lead generation. The agency utilizes AI technology for lead dispute resolution, sales script analysis, and ad scaling to enhance the effectiveness of Local Services Ads. With a focus on maximizing revenue and improving customer service, PrimeLSA helps businesses stand out in local search results and attract high-quality leads.

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.

Cognitive Calls is an AI-powered platform that enables users to automate incoming and outgoing phone and web calls. It offers solutions for various industries such as customer support, appointment scheduling, technical support, real estate, hospitality, insurance, surveys, sales follow-up, recruiting, debt collection, telehealth check-ins, reminders, alerts, voice assistants, learning apps, role-playing scenarios, ecommerce, drive-through systems, automotive systems, and robotic controls. The platform aims to enhance customer interactions by providing personalized support and efficient call handling through voice AI technology.

OneAI is an AI application that offers a Conversational Growth Platform powered by GPT Chatbot technology. It enables users to create and manage GPT Agents for various industries, conduct phone calls, improve customer engagement, embed chatbots on websites, analyze conversations, and more. The platform focuses on driving business KPIs, providing personalized interactions, and enhancing user experience through AI-driven solutions.

Cognosys is an AI-powered assistant that helps you simplify your workflows and automate tasks. With Cognosys, you can hand off tasks to AI Agents, so you can concentrate on what really matters. Cognosys can do more than answer questions. It's capable of breaking down complex objectives by creating tasks for itself and accomplishing them autonomously.

nunu.ai is an AI-powered platform designed to revolutionize game testing by leveraging AI agents to conduct end-to-end tests at scale. The platform allows users to describe what they want to test in plain English, eliminating the need for coding or technical expertise. With features like human-like testing, multi-platform support, and enterprise-grade security, nunu.ai aims to streamline game QA automation, reduce costs, and enhance efficiency for game studios.

Manus is a general AI agent that excels at various tasks in work and life, bridging minds and actions to deliver results. It integrates comprehensive travel information, conducts in-depth stock analysis, develops engaging educational content, generates structured comparison tables, and conducts comprehensive research across extensive networks. Manus works exclusively in the user's best interest, providing actionable insights, visualizations, and customized strategies to increase performance.

Officely AI is an AI application that offers a platform for users to access and utilize various LLM (Large Language Model) models. Users can let these models interact with each other and integrate seamlessly. The platform provides tools, use cases, channels, and pricing options for users to explore and leverage the power of AI in their processes.

CompliantChatGPT is a HIPAA-compliant platform that allows users to utilize OpenAI's GPT models for healthcare-related tasks while maintaining data privacy and security. It anonymizes protected health information (PHI) by replacing it with tokens, ensuring compliance with HIPAA regulations. The platform offers various modes tailored to specific healthcare needs, including bloodwork analysis, PHI anonymization, diagnosis assistance, and treatment planning. CompliantChatGPT streamlines healthcare tasks, enhances productivity, and provides user-friendly assistance through its intuitive interface.

TheLoops is an AI platform designed for Customer Experience (CX) operations, offering a range of AI-powered solutions to enhance agent efficiency, improve customer satisfaction, and streamline processes. The platform integrates with various applications, provides predictive analytics, automates tasks, and offers real-time insights to optimize CX operations. TheLoops is trusted by leading SaaS companies and aims to redefine processes, empower teams, and transform outcomes with efficiency.

Millis AI is an advanced AI tool that enables users to effortlessly create next-gen voice agents with ultra-low latency, providing a seamless and natural conversational experience. It offers affordable pricing, integration with various services through webhooks, and the ability to connect phone numbers to AI voice agents for inbound/outbound calls in over 100 countries. With Millis AI, users can build and deploy voice agents in minutes, from no-code to low-code developers, and transform voice interactions across industries.

Simple AI is an AI application that allows users to build hyper-realistic voice agents and deploy voice AI-powered phone calls in minutes. It offers customization options to fit individual needs, knowledge base search, seamless transfer to human agents, scalability to handle thousands of calls simultaneously, integration with various APIs, and multilingual support. Simple AI is trusted for handling inbound and outbound calls, leads qualification, logistics coordination, customer support, interviewing, sales representation, and receptionist tasks. The application is backed by Y Combinator and supports 29 languages out of the box.

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.

XLeads is a powerful all-in-one wholesaling software designed to provide wholesalers with a competitive edge in the real estate market. It leverages advanced AI technology to analyze data, find motivated sellers and buyers, and streamline the wholesaling process. XLeads offers features such as AI-enhanced data sourcing, CRM tools, advanced disposition platform, and transformative AI for wholesaling success. The software aims to save users time and money by offering comprehensive tools and services for wholesaling real estate.

KeyAI is an AI-powered online platform designed for businesses to enhance customer support, team collaboration, project management, and remote team organization. It offers features such as AI chatbots, video meetings, team management, file sharing, time tracking, and a payment system. KeyAI provides noise-free locations, 24/7 hour support, and easy setup processes. Users can choose from different pricing plans based on their business needs. The platform aims to streamline business operations and improve customer service through innovative AI solutions.

The 'awesome-ai-web-search' repository is a curated list of AI-powered web search software that focuses on the intersection of Large Language Models (LLMs) and web search capabilities. It contains a timeline of various software supporting web search with LLM summarization, chat capabilities, and agent-driven research. The repository showcases both open-source and closed-source tools, providing a comprehensive overview of AI web search solutions available in the market.

Synthora is a lightweight and extensible framework for LLM-driven Agents and ALM research. It aims to simplify the process of building, testing, and evaluating agents by providing essential components. The framework allows for easy agent assembly with a single config, reducing the effort required for tuning and sharing agents. Although in early development stages with unstable APIs, Synthora welcomes feedback and contributions to enhance its stability and functionality.

The Eureka Framework is an open-source toolkit that leverages advanced Artificial Intelligence and Decentralized Science principles to revolutionize scientific discovery. It enables researchers, developers, and decentralized organizations to explore scientific papers, conduct AI-driven experiments, monetize research contributions, provide token-gated access to AI agents, and customize AI agents for specific research domains. The framework also offers features like a RESTful API, robust scheduler for task automation, and webhooks for real-time notifications, empowering users to automate research tasks, enhance productivity, and foster a committed research community.

CrewAI is a cutting-edge framework designed to orchestrate role-playing autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. It enables AI agents to assume roles, share goals, and operate in a cohesive unit, much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI provides the backbone for sophisticated multi-agent interactions. With features like role-based agent design, autonomous inter-agent delegation, flexible task management, and support for various LLMs, CrewAI offers a dynamic and adaptable solution for both development and production workflows.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

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.

Awesome Agents is a curated list of open source AI agents designed for various tasks such as private interactions with documents, chat implementations, autonomous research, human-behavior simulation, code generation, HR queries, domain-specific research, and more. The agents leverage Large Language Models (LLMs) and other generative AI technologies to provide solutions for complex tasks and projects. The repository includes a diverse range of agents for different use cases, from conversational chatbots to AI coding engines, and from autonomous HR assistants to vision task solvers.

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.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

The Awesome-Neuro-Symbolic-Learning-with-LLM repository is a curated collection of papers and resources focusing on improving reasoning and planning capabilities of Large Language Models (LLMs) and Multi-Modal Large Language Models (MLLMs) through neuro-symbolic learning. It covers a wide range of topics such as neuro-symbolic visual reasoning, program synthesis, logical reasoning, mathematical reasoning, code generation, visual reasoning, geometric reasoning, classical planning, game AI planning, robotic planning, AI agent planning, and more. The repository provides a comprehensive overview of tutorials, workshops, talks, surveys, papers, datasets, and benchmarks related to neuro-symbolic learning with LLMs and MLLMs.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

AutoWebGLM is a project focused on developing a language model-driven automated web navigation agent. It extends the capabilities of the ChatGLM3-6B model to navigate the web more efficiently and address real-world browsing challenges. The project includes features such as an HTML simplification algorithm, hybrid human-AI training, reinforcement learning, rejection sampling, and a bilingual web navigation benchmark for testing AI web navigation agents.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Build fast and accurate GenAI applications with GraphRAG SDK, a specialized toolkit for building Graph Retrieval-Augmented Generation (GraphRAG) systems. It integrates knowledge graphs, ontology management, and state-of-the-art LLMs to deliver accurate, efficient, and customizable RAG workflows. The SDK simplifies the development process by automating ontology creation, knowledge graph agent creation, and query handling, enabling users to interact and query their knowledge graphs effectively. It supports multi-agent systems and orchestrates agents specialized in different domains. The SDK is optimized for FalkorDB, ensuring high performance and scalability for large-scale applications. By leveraging knowledge graphs, it enables semantic relationships and ontology-driven queries that go beyond standard vector similarity, enhancing retrieval-augmented generation capabilities.

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.

BeeAI Framework is a versatile tool for building production-ready multi-agent systems. It offers flexibility in orchestrating agents, seamless integration with various models and tools, and production-grade controls for scaling. The framework supports Python and TypeScript libraries, enabling users to implement simple to complex multi-agent patterns, connect with AI services, and optimize token usage and resource management.

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