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.

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.

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.

Chatbot Chatbot is an AI-powered chatbot application designed to provide automated responses to user queries and engage in conversations. It utilizes natural language processing and machine learning algorithms to understand and respond to user inputs effectively. The application is user-friendly and can be integrated into websites or messaging platforms to enhance customer support and engagement.

Ansy.ai is an AI application that offers a self-learning chatbot powered by GPT-3 technology. It integrates with popular communication platforms like Slack and Discord to provide instant and contextual answers to users' questions. Ansy.ai saves time by automating repetitive queries, enhances community engagement with witty responses, and increases productivity by handling minor writing tasks. The application is secure, user-friendly, and continuously learns from user interactions to improve its responses.

Twine is an AI-powered business partner that acts as a virtual receptionist for businesses, helping them capture and respond to leads efficiently. It can handle tasks such as setting appointments, rescheduling, taking payments, and answering customer queries across various communication channels. Twine is designed to work seamlessly with existing software, ensuring that customer information and bookings are synchronized. With its conversational AI capabilities, Twine aims to enhance customer engagement and streamline business operations.

SamurAI bot chat is an AI-powered chatbot application designed to engage users in interactive conversations. The application utilizes advanced natural language processing algorithms to understand and respond to user inputs effectively. With a user-friendly interface, SamurAI bot chat offers a seamless chatting experience for users looking to interact with a virtual assistant. The chatbot is equipped with a wide range of responses and can handle various queries, making it a versatile tool for both personal and business use.

Tiledesk is an AI-powered platform that offers automated customer service solutions with AI agents. It enables businesses to build AI assistants, deploy them across various channels, and streamline customer interactions. Tiledesk helps in automating internal tasks, enhancing support, and achieving tangible results. The platform integrates Generative AI to provide accurate and natural responses, boosting productivity and efficiency. Tiledesk bridges the gap between AI and human support, ensuring seamless customer service experiences.

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.

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.

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.

Bee is an easy and high efficiency ORM framework that simplifies database operations by providing a simple interface and eliminating the need to write separate DAO code. It supports various features such as automatic filtering of properties, partial field queries, native statement pagination, JSON format results, sharding, multiple database support, and more. Bee also offers powerful functionalities like dynamic query conditions, transactions, complex queries, MongoDB ORM, cache management, and additional tools for generating distributed primary keys, reading Excel files, and more. The newest versions introduce enhancements like placeholder precompilation, default date sharding, ElasticSearch ORM support, and improved query capabilities.

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.

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.

Gateway is a tool that streamlines requests to 100+ open & closed source models with a unified API. It is production-ready with support for caching, fallbacks, retries, timeouts, load balancing, and can be edge-deployed for minimum latency. It is blazing fast with a tiny footprint, supports load balancing across multiple models, providers, and keys, ensures app resilience with fallbacks, offers automatic retries with exponential fallbacks, allows configurable request timeouts, supports multimodal routing, and can be extended with plug-in middleware. It is battle-tested over 300B tokens and enterprise-ready for enhanced security, scale, and custom deployments.

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.

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.

Generative BI using RAG on AWS is a comprehensive framework designed to enable Generative BI capabilities on customized data sources hosted on AWS. It offers features such as Text-to-SQL functionality for querying data sources using natural language, user-friendly interface for managing data sources, performance enhancement through historical question-answer ranking, and entity recognition. It also allows customization of business information, handling complex attribution analysis problems, and provides an intuitive question-answering UI with a conversational approach for complex queries.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features such as a Virtual API System with caching and API simulators, a new set of solvable queries determined by LLMs, and a Stable Evaluation System using GPT-4. The Virtual API Server can be set up either by building from source or using a prebuilt Docker image. Users can test the server using provided scripts and evaluate models with Solvable Pass Rate and Solvable Win Rate metrics. The tool also includes model experiments results comparing different models' performance.

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework known for its lightweight design, scalability, and high-speed performance. It offers features like tri-process asynchronous collaboration, Nopad for efficient attention operations, dynamic batch scheduling, FlashAttention integration, tensor parallelism, Token Attention for zero memory waste, and Int8KV Cache. The tool supports various models like BLOOM, LLaMA, StarCoder, Qwen-7b, ChatGLM2-6b, Baichuan-7b, Baichuan2-7b, Baichuan2-13b, InternLM-7b, Yi-34b, Qwen-VL, Llava-7b, Mixtral, Stablelm, and MiniCPM. Users can deploy and query models using the provided server launch commands and interact with multimodal models like QWen-VL and Llava using specific queries and images.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

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