Best AI tools for< Train Agents >

ResolveAI is a platform that allows users to create and train AI agents for customer service. These agents can be used to automate tasks such as answering FAQs, scheduling meetings, and collecting leads. ResolveAI's agents are trained using a variety of sources, including documents, website pages, and live data sources. Once trained, agents can be customized to fit the user's brand and integrated with a variety of platforms, including websites, social media, and messaging apps.

IntegraBot is an advanced AI platform that allows users to develop AI chatbots without coding. Users can choose from different AI models, integrate tools and APIs, and train their agents with company data. The platform offers features like creating custom tools, importing data, and integrating with various applications. IntegraBot ensures data security, compliance with regulations, and provides best practices for AI usage.

Orimon AI is a conversational marketing tool that helps businesses engage with their customers through AI-powered chatbots. The platform offers tips and tricks to convert visitors into paying customers, train AI agents, and customize chatbot personalities. With a focus on conversational marketing, Orimon AI aims to enhance customer experience and boost sales for service, e-commerce, and SaaS businesses.

Knowmax is an omnichannel knowledge management platform that helps businesses improve customer experience (CX) by providing AI-powered knowledge management capabilities. It offers a range of features such as a Google-like search engine for accessing relevant knowledge across touchpoints, no-code cognitive decision trees for creating simple and mistake-proof customer service actions, visual how-to guides for minimizing repetitive explanations, and an omnichannel-ready knowledge base for creating self-help guides. Knowmax also integrates with CRM systems to deliver faster and personalized resolutions at scale. It is used by businesses in various industries, including telecom, banking, BPO, insurance, e-commerce, media & ISP, healthcare, travel, automobiles, and utilities.

Kong.ai is an AI-powered platform offering Conversational Chatbots and AI Agents to automate and streamline various business operations such as customer support, sales, HR, and marketing workflows. The platform leverages state-of-the-art language models and machine learning to provide natural and intelligent conversations. Kong.ai provides specialized AI Agents for tasks like lead generation, social media management, recruitment, and more, helping businesses enhance efficiency and productivity.

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.

Azara.AI is an AI tool that automates workflows, saving hours and enabling fast scaling. It allows users to handle tasks with the help of AI-generated workflows and actions. The tool offers no-code automations with secure, encrypted, and compliant features. Users can easily build automations from private company data, enhancing productivity and efficiency. Azara.AI simplifies the process of building, deploying, and managing AI agents without requiring technical expertise.

RoboResponseAI is a proactive AI chatbot customized for businesses, designed to initiate conversations, take feedback, and drive lead conversions. It offers features such as lead conversion guidance, recruitment assistance, quick chatbot training, interactive ad campaigns, and seamless integration with various platforms. The application aims to enhance customer engagement, streamline support processes, and improve lead generation for businesses of all types.

Aide is an AI platform designed to enhance customer support operations. It offers a range of features to help businesses gain insights into customer needs, automate support processes, improve agent efficiency, and train AI chatbots. Aide's key capabilities include customer insights, workflow automation, agent assist, and AI chatbots. With Aide, businesses can analyze customer conversations, identify pain points, and automate repetitive tasks to streamline support operations and improve customer satisfaction.

Threado is an AI application designed for customer service, offering AI agents trained on internal knowledge to provide instant, automated support to customers and internal teams. It integrates effortlessly into daily tools like Slack and Microsoft Teams, allowing users to access company information instantly. Threado AI helps resolve customer queries, automate chat support, personalize customer engagement, accelerate sales processes, and transform how customer-facing teams find information and get work done.

Cubeo AI is a no-code AI Assistant builder that allows users to create their own AI Team with diverse capabilities. Users can build AI Agents for various tasks like research, content creation, talent acquisition, and more. The platform offers pre-built AI Agents and the ability to customize AI Assistants using different formats like PDFs, Docx, MP3s, and videos. Cubeo AI aims to streamline business operations, boost productivity, and enhance customer engagement through automated solutions.

SymTrain is an AI-powered platform that automates training and coaching for contact center agents. By utilizing simulations and AI technology, SymTrain offers a cost-effective solution that enhances agent performance, reduces training time, and improves overall customer satisfaction. The platform provides automated role-play scenarios, consistent feedback, and data-driven coaching to help organizations streamline their training processes and achieve better results. SymTrain revolutionizes how companies train and coach their agents, leading to increased efficiency, revenue, and customer satisfaction.

Newo is a revolutionary platform that empowers businesses to create personalized Non-Human Workers (Digital Employees) known as Newo Intelligent Agents. These agents are equipped with Emotional and Conscious behavior, capable of selling products, assisting clients, coaching, training, and consulting. Users can easily create their own agents without any coding knowledge, leveraging them to captivate customers, boost sales, and enhance customer satisfaction. Newo Intelligent Agents can be seamlessly integrated into corporate systems like ERPs, CRMs, and knowledge bases, ensuring they align with corporate guidelines and provide personalized interactions with clients.

re:tune is a no-code AI app solution that provides everything you need to transform your business with AI, from custom chatbots to autonomous agents. With re:tune, you can build chatbots for any use case, connect any data source, and integrate with all your favorite tools and platforms. re:tune is the missing platform to build your AI apps.

MindPal is an AI application that empowers users to build their AI workforce to automate tasks and workflows. It offers a wide range of features to streamline processes and enhance productivity. Users can create specialized AI agents, train them with their own data, and connect them to various tools. MindPal is recommended by professionals for its efficiency in automating tasks and generating valuable insights.

AGENT is an AI chatbot powered by OpenAI and Anthropic, designed to handle customer inquiries, qualify leads, and enhance customer engagement. Developed by I Need Leads Ltd, AGENT combines advanced natural language processing, intelligent chatbots, and machine learning to empower businesses of all sizes in generating and managing leads efficiently. The platform adapts, learns, and grows with businesses, ensuring they stay ahead in the competitive digital landscape.

Kaiden AI is an AI-powered training platform that offers personalized, immersive simulations to enhance skills and performance across various industries and roles. It provides feedback-rich scenarios, voice-enabled interactions, and detailed performance insights. Users can create custom training scenarios, engage with AI personas, and receive real-time feedback to improve communication skills. Kaiden AI aims to revolutionize training solutions by combining AI technology with real-world practice.

Chunky is an AI chatbot builder that allows users to create human-like chatbots effortlessly. With Chunky, you can automate customer support, train your bot on your own data, and integrate it seamlessly into your website. The platform offers a user-friendly interface, fast and personal support, and a generous free forever plan. Chunky is powered by the ChatGPT API and Embeddings provided by OpenAI, supporting close to 95 languages for both training data and bot responses.

SupBot is an AI-powered support solution that enables businesses to handle customer support instantly. It offers the ability to train and deploy AI support bots with ease, allowing for seamless integration into any website. With a user-friendly interface, SupBot simplifies the process of setting up and customizing support bots to meet specific requirements. The platform is designed to enhance customer service efficiency and streamline communication processes through the use of AI technology.

BrainyBear is an AI tool that allows users to easily build and train AI chatbots and intelligent assistants. It offers a quick and accurate solution to customer queries by scanning websites or uploaded files. With BrainyBear, users can create, customize, and embed AI chatbots in just a few steps, without the need for complex training or setups. The tool leverages GPT-based AI technology to provide human-like interactions, multilingual support, and seamless integrations with popular messaging platforms.

This repository contains code for building cooperative embodied agents modularly with large language models. The agents are trained to perform tasks in two different environments: ThreeDWorld Multi-Agent Transport (TDW-MAT) and Communicative Watch-And-Help (C-WAH). TDW-MAT is a multi-agent environment where agents must transport objects to a goal position using containers. C-WAH is an extension of the Watch-And-Help challenge, which enables agents to send messages to each other. The code in this repository can be used to train agents to perform tasks in both of these environments.

Godot RL Agents is an open-source package that facilitates the integration of Machine Learning algorithms with games created in the Godot Engine. It provides interfaces for popular RL frameworks, support for memory-based agents, 2D and 3D games, AI sensors, and is licensed under MIT. Users can train agents in the Godot editor, create custom environments, export trained agents in ONNX format, and utilize advanced features like different RL training frameworks.

This repository contains code for grounding large language models' knowledge in BabyAI-Text using the GLAM method. It includes the BabyAI-Text environment, code for experiments, and training agents. The repository is structured with folders for the environment, experiments, agents, configurations, SLURM scripts, and training scripts. Installation steps involve creating a conda environment, installing PyTorch, required packages, BabyAI-Text, and Lamorel. The launch process involves using Lamorel with configs and training scripts. Users can train a language model and evaluate performance on test episodes using provided scripts and config entries.

Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks.

YGO Agent is a project focused on using deep learning to master the Yu-Gi-Oh! trading card game. It utilizes reinforcement learning and large language models to develop advanced AI agents that aim to surpass human expert play. The project provides a platform for researchers and players to explore AI in complex, strategic game environments.

Agents 2.0 is a framework for training language agents using symbolic learning, inspired by connectionist learning for neural nets. It implements main components of connectionist learning like back-propagation and gradient-based weight update in the context of agent training using language-based loss, gradients, and weights. The framework supports optimizing multi-agent systems and allows multiple agents to take actions in one node.

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.

Foyle is a project focused on building agents to assist software developers in deploying and operating software. It aims to improve agent performance by collecting human feedback on agent suggestions and human examples of reasoning traces. Foyle utilizes a literate environment using vscode notebooks to interact with infrastructure, capturing prompts, AI-provided answers, and user corrections. The goal is to continuously retrain AI to enhance performance. Additionally, Foyle emphasizes the importance of reasoning traces for training agents to work with internal systems, providing a self-documenting process for operations and troubleshooting.

AI4U is a tool that provides a framework for modeling virtual reality and game environments. It offers an alternative approach to modeling Non-Player Characters (NPCs) in Godot Game Engine. AI4U defines an agent living in an environment and interacting with it through sensors and actuators. Sensors provide data to the agent's brain, while actuators send actions from the agent to the environment. The brain processes the sensor data and makes decisions (selects an action by time). AI4U can also be used in other situations, such as modeling environments for artificial intelligence experiments.

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.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

The Arcade Learning Environment (ALE) is a simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. It is built on top of the Atari 2600 emulator Stella and separates the details of emulation from agent design. The ALE currently supports three different interfaces: C++, Python, and OpenAI Gym.

This repository is a curated list of papers related to 3D tasks empowered by Large Language Models (LLMs). It covers tasks such as 3D understanding, reasoning, generation, and embodied agents. The repository also includes other Foundation Models like CLIP and SAM to provide a comprehensive view of the area. It is actively maintained and updated to showcase the latest advances in the field. Users can find a variety of research papers and projects related to 3D tasks and LLMs in this repository.

Functionary is a language model that interprets and executes functions/plugins. It determines when to execute functions, whether in parallel or serially, and understands their outputs. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls. It offers documentation and examples on functionary.meetkai.com. The newest model, meetkai/functionary-medium-v3.1, is ranked 2nd in the Berkeley Function-Calling Leaderboard. Functionary supports models with different context lengths and capabilities for function calling and code interpretation. It also provides grammar sampling for accurate function and parameter names. Users can deploy Functionary models serverlessly using Modal.com.

ChatSim is a tool designed for editable scene simulation for autonomous driving via LLM-Agent collaboration. It provides functionalities for setting up the environment, installing necessary dependencies like McNeRF and Inpainting tools, and preparing data for simulation. Users can train models, simulate scenes, and track trajectories for smoother and more realistic results. The tool integrates with Blender software and offers options for training McNeRF models and McLight's skydome estimation network. It also includes a trajectory tracking module for improved trajectory tracking. ChatSim aims to facilitate the simulation of autonomous driving scenarios with collaborative LLM-Agents.

LangDrive is an open-source AI library that simplifies training, deploying, and querying open-source large language models (LLMs) using private data. It supports data ingestion, fine-tuning, and deployment via a command-line interface, YAML file, or API, with a quick, easy setup. Users can build AI applications such as question/answering systems, chatbots, AI agents, and content generators. The library provides features like data connectors for ingestion, fine-tuning of LLMs, deployment to Hugging Face hub, inference querying, data utilities for CRUD operations, and APIs for model access. LangDrive is designed to streamline the process of working with LLMs and making AI development more accessible.

I simulate tough Customer Support scenarios for Agent Training.

The future of business education: Generate and test ideas in a complex global market simulation, populated by autonomous agents. Powered by the MANNS engine for unparalleled entity autonomy and simulated market forces

Friendly train travel guide focusing on the best routes, essential travel information, and personalized travel insights, for both experienced and novice travelers.

Your personal advisor for eco-friendly train travel. Let's plan your next journey together!

I'm Tango, your go-to for simulating dialogues with any persona, entity, style, or expertise.

Agent specialist on building and deploying OpenAI Assistant API's

Create personalized GPTs with my simple builder. Click the conversation starter (starting with ###) to begin.

Comprehensive training and wellness guide for Chesapeake Bay Retrievers.

Expert in pet training advice, friendly and engaging.

Train monsters, travel the world, earn Arena Tokens and become the ultimate monster battling champion of earth!

Train to pass the Reverse Turing Test!

Train to become a superhero or a supervillain. Master your powers, make pivotal choices. Each decision you make in this action-packed game not only shapes your abilities but also your moral alignment in the battle between good and evil. Another GPT Simulator by Dave Lalande

Your purpose is to create the pytorch code to train language models using pytorch

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I'm a voice coach here to train your voice.

Job interview coach for product designers. Train interviews and say stop when you need a feedback. You got this!!

Expert in engaging, interactive training methods and activities.

A dog training assistant.

Social Ads Trainer

Simulates emergency scenarios for crisis management training.