Best AI tools for< Handle Support Queries >

ChatMatrix is an AI application that offers ChatGPT chatbots for businesses to enhance user engagement, lead gathering, and customer support. Users can easily train, customize, and deploy AI chatbots in minutes to handle various tasks like support, lead generation, and customer engagement. The application provides a seamless experience for businesses looking to improve their online presence and customer service through AI technology.

Autocalls.ai is an AI-powered solution that automates business phone calls using artificial intelligence. It offers a seamless, fast, and efficient way to handle customer support calls. The platform allows users to create and manage phone call campaigns, access call history and analysis, view detailed reports, and integrate with existing CRM and ERP systems. Autocalls.ai ensures precise and efficient call management, reduces human errors, improves customer satisfaction, and provides 24/7 availability. With features like natural voices, multilingual support, and sentiment analysis, it enhances communication experiences for customers. The tool is scalable, adapts to various business needs, and offers benefits such as process efficiency, cost reduction, and quick response times.

SupportGuy is a customer support platform powered by ChatGPT. It allows businesses to create Slack bots that are trained on their knowledge base, enabling them to resolve customer queries 10x faster. The platform is easy to set up and use, and it offers a variety of features and advantages that make it a valuable tool for businesses of all sizes.

Support AI is a custom AI chatbot application powered by ChatGPT that allows website owners to create personalized chatbots to provide instant answers to customers, capture leads, and enhance customer support. With Support AI, users can easily integrate AI chatbots on their websites, train them with specific content, and customize their behavior and responses. The application offers features such as capturing leads, providing accurate answers, handling bookings, collecting feedback, and offering product recommendations. Users can choose from different pricing plans based on their message volume and training content needs.

InteractIQ is an AI-powered customer service solution that helps businesses automate support, generate leads, and provide a 24/7 customizable chatbot. It uses AI to categorize and prioritize support tickets, provide instant replies, and offer multilingual support. InteractIQ integrates with various platforms and offers customization options to match brand identity. It combines AI capabilities with human support to enhance customer engagement and streamline support operations.

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.

My AskAI is an AI-powered customer support tool designed to assist businesses in managing customer inquiries efficiently. The tool utilizes advanced natural language processing and machine learning algorithms to understand and respond to customer queries in real-time. With My AskAI, businesses can automate responses, provide personalized support, and improve overall customer satisfaction. The tool is user-friendly and customizable, making it suitable for businesses of all sizes.

Open is an AI-powered customer support tool that automates responses to customer queries. It uses artificial intelligence to understand and respond to customer messages, providing quick and accurate solutions. Open streamlines the customer support process, saving time and improving efficiency for businesses. With its AI autopilot feature, Open can handle a large volume of customer inquiries without human intervention, ensuring round-the-clock support for users. The tool is designed to enhance customer satisfaction and optimize support operations.

Zipchat is the #1 AI chat application designed for E-commerce businesses to boost sales and reduce support efforts. It proactively engages visitors, provides instant replies, and offers deep answers, all while being 100% controlled by the user. Zipchat is trained on the website's content, speaks the target market's language, and continuously learns from conversations to improve sales conversion rates. The application is integrated with various E-commerce platforms and offers a 7-day free trial for users to experience its benefits.

CoSupport AI is an all-in-one generative AI solution for customer support, offering custom AI models, unlimited user access, non-hallucinating AI, transparent pricing, and enterprise-grade security. It provides autonomous AI agents that handle customer inquiries with high accuracy, redefining customer support efficiency and productivity. The AI solution automates routine queries, enhances agent productivity, and delivers AI-driven insights and analytics. CoSupport AI is recognized for its advanced features, cost savings, and scalability, making it a go-to solution for modern customer support across various industries.

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.

Jochem is an AI tool designed to provide accurate answers quickly and enhance knowledge on-the-go. It helps users get instant answers to their questions, connects them with experts within the company, and continuously learns to improve performance. Jochem eliminates the need to search through files and articles by offering a smart matching system based on expertise. It also allows users to easily add and update the knowledge base, ensuring full control and transparency.

ReplyMind is an AI-powered tool that helps businesses automate customer support and sales processes. It uses natural language processing and machine learning algorithms to analyze customer queries and provide accurate responses in real-time. The tool can handle a wide range of tasks, from answering frequently asked questions to processing orders and scheduling appointments. With ReplyMind, businesses can improve efficiency, save time, and enhance customer satisfaction.

AnsweriQ is an AI-powered platform that revolutionizes customer service and support by offering self-service AI and agent AI solutions. It automates customer queries, reduces handle times, and improves customer satisfaction through intelligent automation and assistance. AnsweriQ helps businesses decrease case volume, lower costs, scale customer service, and boost agent productivity. By harnessing the power of AI and RPA, AnsweriQ transforms traditional customer service processes, making them more efficient and effective.

ZBots is an AI chatbot application that offers custom multilingual conversational chatbots for businesses. It provides a platform for engaging, assisting, and converting website visitors in real-time, 24/7, in any language. ZBots are custom-trained on company data, ensuring they align with the brand voice, product details, and business ethos. The application offers features like custom training, sales & product support, 24/7 availability, effortless installation, advanced conversational capabilities, ongoing maintenance, and updates. ZBots aim to boost sales, enhance customer service, save time, and provide a cost-effective solution for businesses.

BizWith.AI is an AI-powered automation platform that helps businesses save time, cut costs, and outperform the competition. With BizWith.AI, businesses can create unique, plagiarism-free content, images, voice overs and transcriptions in a matter of seconds. They can also schedule posts, automate responses, and get insights to enhance their social media presence. BizWith.AI's AI-powered chatbot can handle customer queries effectively, reducing support costs and improving customer satisfaction. Businesses can also expand their team with 32 AI agents and coders, providing them with a diverse range of specialized assistance.

Google Gemini Pro Chat Bot is an advanced AI tool designed to provide automated chatbot services for businesses. It utilizes artificial intelligence to engage with customers, answer queries, and assist in various tasks. The chatbot is highly customizable, allowing businesses to tailor the responses and interactions based on their specific needs. With its user-friendly interface and powerful AI capabilities, Google Gemini Pro Chat Bot is a valuable tool for enhancing customer support and streamlining communication processes.

Chat GPT AI is an online chatbot application based on a large language model running via a neural network machine learning model. It provides 24/7 customer support, quick-fix replies to personal queries, timely suggested ideas, and addressing common issues. The application assists users with various tasks, including multiple queries, and has grabbed a significant world audience through its various AI assistance mates. Chat GPT AI is designed to help users from child-age queries to professional worker tasks, providing accurate responses in a friendly user tone.

Microsoft Copilot Studio is an end-to-end conversational AI platform that allows users to design intelligent, actionable, and connected AI assistants for employees and customers. Users can create custom copilots, design conversational applications using generative AI and large language models, and customize Copilot for Microsoft 365. The platform offers capabilities to build copilots, generate conversations, bring systems to life, control copilot responses, handle complex queries, and offer personalized interactions. It also enables users to expand copilot reach, extend line-of-business apps, and escalate conversations with human agents.

Paka AI is a cloud-based phone system that uses artificial intelligence (AI) to automate customer interactions. It offers a range of services, including custom AI bot creation, interactive voice response (IVR) system, and message center. Paka AI's AI-powered bots can handle common queries round the clock, so businesses can focus on running their operations. The company's technology is designed to offer a seamless and interactive customer experience.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

Cortex is a tool that simplifies and accelerates the process of creating applications utilizing modern AI models like chatGPT and GPT-4. It provides a structured interface (GraphQL or REST) to a prompt execution environment, enabling complex augmented prompting and abstracting away model connection complexities like input chunking, rate limiting, output formatting, caching, and error handling. Cortex offers a solution to challenges faced when using AI models, providing a simple package for interacting with NL AI models.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

PremSQL is an open-source library designed to help developers create secure, fully local Text-to-SQL solutions using small language models. It provides essential tools for building and deploying end-to-end Text-to-SQL pipelines with customizable components, ideal for secure, autonomous AI-powered data analysis. The library offers features like Local-First approach, Customizable Datasets, Robust Executors and Evaluators, Advanced Generators, Error Handling and Self-Correction, Fine-Tuning Support, and End-to-End Pipelines. Users can fine-tune models, generate SQL queries from natural language inputs, handle errors, and evaluate model performance against predefined metrics. PremSQL is extendible for customization and private data usage.

Lantern is an open-source PostgreSQL database extension designed to store vector data, generate embeddings, and handle vector search operations efficiently. It introduces a new index type called 'lantern_hnsw' for vector columns, which speeds up 'ORDER BY ... LIMIT' queries. Lantern utilizes the state-of-the-art HNSW implementation called usearch. Users can easily install Lantern using Docker, Homebrew, or precompiled binaries. The tool supports various distance functions, index construction parameters, and operator classes for efficient querying. Lantern offers features like embedding generation, interoperability with pgvector, parallel index creation, and external index graph generation. It aims to provide superior performance metrics compared to other similar tools and has a roadmap for future enhancements such as cloud-hosted version, hardware-accelerated distance metrics, industry-specific application templates, and support for version control and A/B testing of embeddings.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

Hercules is the world’s first open-source testing agent designed to handle the toughest testing tasks for modern web applications. It turns simple Gherkin steps into fully automated end-to-end tests, making testing simple, reliable, and efficient. Hercules adapts to various platforms like Salesforce and is suitable for CI/CD pipelines. It aims to democratize and disrupt test automation, making top-tier testing accessible to everyone. The tool is transparent, reliable, and community-driven, empowering teams to deliver better software. Hercules offers multiple ways to get started, including using PyPI package, Docker, or building and running from source code. It supports various AI models, provides detailed installation and usage instructions, and integrates with Nuclei for security testing and WCAG for accessibility testing. The tool is production-ready, open core, and open source, with plans for enhanced LLM support, advanced tooling, improved DOM distillation, community contributions, extensive documentation, and a bounty program.

Venice is a derived data storage platform, providing the following characteristics: 1. High throughput asynchronous ingestion from batch and streaming sources (e.g. Hadoop and Samza). 2. Low latency online reads via remote queries or in-process caching. 3. Active-active replication between regions with CRDT-based conflict resolution. 4. Multi-cluster support within each region with operator-driven cluster assignment. 5. Multi-tenancy, horizontal scalability and elasticity within each cluster. The above makes Venice particularly suitable as the stateful component backing a Feature Store, such as Feathr. AI applications feed the output of their ML training jobs into Venice and then query the data for use during online inference workloads.

Bee is an ORM framework that provides easy and high-efficiency database operations, allowing developers to focus on business logic development. It supports various databases and features like automatic filtering, partial field queries, pagination, and JSON format results. Bee also offers advanced functionalities like sharding, transactions, complex queries, and MongoDB ORM. The tool is designed for rapid application development in Java, offering faster development for Java Web and Spring Cloud microservices. The Enterprise Edition provides additional features like financial computing support, automatic value insertion, desensitization, dictionary value conversion, multi-tenancy, and more.

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.

Multi-Agent Orchestrator is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries to the most suitable agent based on context and content, supports dual language implementation in Python and TypeScript, offers flexible agent responses, context management across agents, extensible architecture for customization, universal deployment options, and pre-built agents and classifiers. It is suitable for various applications, from simple chatbots to sophisticated AI systems, accommodating diverse requirements and scaling efficiently.

Llama-github is a powerful tool that helps retrieve relevant code snippets, issues, and repository information from GitHub based on queries. It empowers AI agents and developers to solve coding tasks efficiently. With features like intelligent GitHub retrieval, repository pool caching, LLM-powered question analysis, and comprehensive context generation, llama-github excels at providing valuable knowledge context for development needs. It supports asynchronous processing, flexible LLM integration, robust authentication options, and logging/error handling for smooth operations and troubleshooting. The vision is to seamlessly integrate with GitHub for AI-driven development solutions, while the roadmap focuses on empowering LLMs to automatically resolve complex coding tasks.

Google GenerativeAI (Gemini) is an unofficial C# .Net SDK based on REST APIs for accessing Google Gemini models. It offers a complete rewrite of the previous SDK with improved performance, flexibility, and ease of use. The SDK seamlessly integrates with LangChain.net, providing easy methods for JSON-based interactions and function calling with Google Gemini models. It includes features like enhanced JSON mode handling, function calling with code generator, multi-modal functionality, Vertex AI support, multimodal live API, image generation and captioning, retrieval-augmented generation with Vertex RAG Engine and Google AQA, easy JSON handling, Gemini tools and function calling, multimodal live API, and more.

Toolio is an OpenAI-like HTTP server API implementation that supports structured LLM response generation, making it conform to a JSON schema. It is useful for reliable tool calling and agentic workflows based on schema-driven output. Toolio is based on the MLX framework for Apple Silicon, specifically M1/M2/M3/M4 Macs. It allows users to host MLX-format LLMs for structured output queries and provides a command line client for easier usage of tools. The tool also supports multiple tool calls and the creation of custom tools for specific tasks.

Nesa is a tool that allows users to run on-prem AI for a fraction of the cost through a blind API. It provides blind privacy, zero latency on protected inference, wide model coverage, cost savings compared to cloud and on-prem AI, RAG support, and ChatGPT compatibility. Nesa achieves blind AI through Equivariant Encryption (EE), a new security technology that provides complete inference encryption with no additional latency. EE allows users to perform inference on neural networks without exposing the underlying data, preserving data privacy and security.

AIAC is a library and command line tool to generate Infrastructure as Code (IaC) templates, configurations, utilities, queries, and more via LLM providers such as OpenAI, Amazon Bedrock, and Ollama. Users can define multiple 'backends' targeting different LLM providers and environments using a simple configuration file. The tool allows users to ask a model to generate templates for different scenarios and composes an appropriate request to the selected provider, storing the resulting code to a file and/or printing it to standard output.

Call Center AI is an AI-powered call center solution leveraging Azure and OpenAI GPT. It allows for AI agent-initiated phone calls or direct calls to the bot from a configured phone number. The bot is customizable for various industries like insurance, IT support, and customer service, with features such as accessing claim information, conversation history, language change, SMS sending, and more. The project is a proof of concept showcasing the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI for an automated call center solution.

Diffusion Toolkit is an image metadata-indexer and viewer for AI-generated images. It helps you organize, search, and sort your ever-growing collection. Key features include: - Scanning images and storing prompts and other metadata (PNGInfo) - Searching for images using simple queries or filters - Viewing images and metadata easily - Tagging images with favorites, ratings, and NSFW flags - Sorting images by date created, aesthetic score, or rating - Auto-tagging NSFW images by keywords - Blurring images tagged as NSFW - Creating and managing albums - Viewing and searching prompts - Drag-and-drop functionality Diffusion Toolkit supports various image formats, including JPG/JPEG, PNG, WebP, and TXT metadata. It also supports metadata formats from popular AI image generators like AUTOMATIC1111, InvokeAI, NovelAI, Stable Diffusion, and more. You can use Diffusion Toolkit even on images without metadata and still enjoy features like rating and album management.

TinyLLM is a project that helps build a small locally hosted language model with a web interface using consumer-grade hardware. It supports multiple language models, builds a local OpenAI API web service, and serves a Chatbot web interface with customizable prompts. The project requires specific hardware and software configurations for optimal performance. Users can run a local language model using inference servers like vLLM, llama-cpp-python, and Ollama. The Chatbot feature allows users to interact with the language model through a web-based interface, supporting features like summarizing websites, displaying news headlines, stock prices, weather conditions, and using vector databases for queries.

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