Amico is an AI agent framework that lets users create custom autonomous assistants for various business processes. Through a visual flow builder, users define triggers such as email arrival or webhook events, connect to third-party APIs, and program logic for data processing, classification, and response generation. The platform supports integrations with Slack, Zendesk, Google Sheets, and more, enabling agents to ingest data, perform sentiment analysis, schedule meetings, or generate reports. Agents can run on schedules or react to events in real time, executing tasks without human intervention. Advanced features include conversational conversations, multi-step workflows, and performance analytics dashboards. With built-in security and role-based access, Amico offers a scalable solution for automating repetitive tasks and improving efficiency across teams.

Anda AI lets you design, train, and deploy virtual agents that connect to your tools—email, CRM, spreadsheets, chat apps, and more—and perform rule-based or AI-driven tasks automatically. Define triggers, workflows, and data mappings via a visual builder, then monitor agent performance through real-time dashboards. Use cases include email triage, automated reporting, invoice processing, social listening, and CRM updates, all running 24/7 without coding.

APIDNA is an innovative platform that utilizes autonomous AI agents to automate the process of API integration. The platform caters to developers and businesses, enabling rapid integration mastery with various service providers. APIDNA’s AI agents map client requests effortlessly and manage API responses, ensuring smooth data handling. It also offers instant code generation, real-time monitoring, comprehensive testing, and scalable solutions. Coupled with a user-friendly interface, APIDNA ensures that integrations are hassle-free, secure, and efficient. The platform’s adaptive AI learning and customizable workflows further enhance productivity and innovation.

bedrock-agent is a versatile AI agent framework that integrates with AWS Bedrock’s suite of large language models to orchestrate complex, task-driven workflows. It offers a plugin architecture for registering custom tools, memory modules for context persistence, and a chain-of-thought mechanism for improved reasoning. Through a simple Python API and command-line interface, it enables developers to define agents that can call external services, process documents, generate code, or interact with users via chat. Agents can be configured to automatically select relevant tools based on user prompts and maintain conversational state across sessions. This framework is open-source, extensible, and optimized for rapid prototyping and deployment of AI-powered assistants on local or AWS cloud environments.

Adaline AI is a SaaS platform for designing, training, and deploying AI agents without writing code. Users define agent tasks and conversation flows via an intuitive drag-and-drop builder, then connect to data sources like CRM systems, email, calendars, and messaging platforms. The agents leverage natural language processing to interpret user requests, perform actions across integrated services, and generate accurate responses. Built-in analytics help monitor performance and refine agent behavior over time.

HexarAI is an all-in-one AI platform that revolutionizes the way businesses operate. It integrates marketing, tech development, accounting, and design into a seamless experience designed to optimize performance. With advanced analytics, customizable workflows, and AI-driven insights, HexarAI enables businesses to harness data effectively, making informed decisions that drive growth. The platform's user-friendly interface and flexible features ensure that companies of all sizes can leverage AI to enhance productivity and streamline operations.

Indigo offers a powerful AI copilot for high-performance teams, enabling them to build custom AI tools and workflows designed to boost productivity. With access to leading models from top providers, Indigo allows for seamless data integration, custom AI commands from a marketplace, and efficient team management. The platform's assistant mode provides advanced organizational context, while features like smart highlights, vision commands, and clipboard inputs enhance user experience across various applications.

NanoBrowser runs directly in your browser as a Chrome extension, enabling you to automate repetitive or complex web tasks via natural-language prompts. You configure it with your own LLM API key—OpenAI GPT, self-hosted LLaMA models, or others—and define workflows composed of multiple agents. It supports data scraping, form interactions, automated research, and workflow chaining through LangChain integration. You can orchestrate agents to collaborate on subtasks, export results in CSV or JSON, and debug or refine steps interactively. As an open-source alternative to proprietary operators, NanoBrowser prioritizes privacy, extensibility, and ease of use.

Otron is an AI-driven email management solution designed to streamline workflows and boost productivity. It features a free email ticketing system that helps teams organize emails into actionable tickets. The platform includes a smart AI assistant for content analysis, task creation, and response drafting. Users can also design custom workflows using a node-based visual builder, enabling automated responses and real-time data-driven insights.

SageFlow automates workflow processes, enabling users to design and optimize workflows without needing extensive programming knowledge. It connects with various applications to facilitate task automation, enhance productivity, and ensure a seamless flow of information between tools. Users can create custom workflows tailored to their specific needs, allowing for a more efficient operation across teams and departments.

SelfYAI offers a comprehensive, no-code interface for designing, training, and deploying AI agents tailored to your specific business needs. Users can import data from CRM systems, spreadsheets, and databases, then configure custom workflows and conversational flows with simple drag-and-drop tools. Agents maintain context using memory modules and can be deployed across websites, Slack, Teams, and API endpoints. Built-in analytics track interaction volume, resolution rates, and user feedback, supporting iterative improvements. With robust security features and role-based access controls, SelfYAI ensures data privacy and compliance while scaling AI-driven automation effortlessly.

The Ten AI Agent platform provides a graphical builder where users connect various data sources—cloud documents, databases, or APIs—and define an agent’s purpose and tone. Agents can answer user queries with context-aware responses, summarize large documents on demand, and trigger automated workflows such as ticket creation or email notifications. A built-in analytics dashboard tracks usage, performance, and user satisfaction. Agents can be customized with unique personalities and fine-tuned prompts without writing code. Once ready, they can be deployed via embed code, REST APIs, or integrations with Slack, MS Teams, and other messaging platforms to deliver seamless conversational experiences across channels.

Airtable is a cloud-based tool that merges the features of spreadsheets and databases into one flexible platform. Users can create tailored workflows, store, track, and analyze data efficiently across teams. It offers various templates and customization options, making it suitable for personal to enterprise-level applications. Airtable integrates seamlessly with numerous other tools and services, aiming to simplify data management and improve productivity, collaboration, and data visualization.

AgenticRAG provides a modular architecture for creating autonomous agents that leverage retrieval-augmented generation (RAG). It offers components to index documents in vector stores, retrieve relevant context, and feed it into LLMs to generate context-aware responses. Users can integrate external APIs and tools, configure memory stores to track conversation history, and define custom workflows to orchestrate multi-step decision-making processes. The framework supports popular vector databases like Pinecone and FAISS, and LLM providers such as OpenAI, allowing seamless switching or multi-model setups. With built-in abstractions for agent loops and tool management, AgenticRAG simplifies development of agents capable of tasks like document QA, automated research, and knowledge-driven automation, reducing boilerplate code and accelerating time to deployment.

Agent-FLAN is designed to simplify the creation of sophisticated AI agent-driven applications by segmenting tasks into planning and execution roles. Users define agent behaviors and workflows via configuration files, specifying input formats, tool interfaces, and communication protocols. The planning agent generates high-level task plans, while execution agents carry out specific actions, such as calling APIs, processing data, or generating content with large language models. Agent-FLAN’s modular architecture supports plug-and-play tool adapters, custom prompt templates, and real-time monitoring dashboards. It seamlessly integrates with popular LLM providers like OpenAI, Anthropic, and Hugging Face, enabling developers to quickly prototype, test, and deploy multi-agent workflows for scenarios such as automated research assistants, dynamic content generation pipelines, and enterprise process automation.

Agentic App Template is a fully configured Next.js project that serves as a foundation for developing AI-driven agentic applications. It incorporates a modular folder structure, environment variable management, and example agent workflows leveraging OpenAI’s GPT models and vector databases like Pinecone. The template demonstrates key patterns such as sequential multi-step chains, conversational Q&A agents, and text generation endpoints. Developers can easily customize chain logic, integrate additional services, and deploy to platforms like Vercel or Netlify. With TypeScript support and built-in error handling, the scaffold reduces initial setup time and provides clear documentation for further extension.

AgentReader is a developer-friendly AI agent framework that enables you to load and index various data sources such as PDFs, text files, markdown documents, and web pages. It integrates seamlessly with major LLM providers to power interactive chat sessions and question-answering over your knowledge base. Features include real-time streaming of model responses, customizable retrieval pipelines, web scraping via headless browser, and a plugin architecture for extending ingestion and processing capabilities.

Botpress is an open-source chatbot development platform designed for developers to build and manage conversational agents. It supports natural language understanding, dialogue management, and integrated machine learning modules. Users can create custom workflows and integrate them with external APIs. With Botpress, businesses can deploy chatbots on various platforms, enhancing customer engagement and automating customer service effectively.

This project demonstrates a comprehensive framework for creating retrieval-augmented AI agents using LlamaIndex. It guides developers through the entire workflow, starting with document ingestion and vector store creation, followed by defining a custom agent loop for contextual question-answering. Leveraging LlamaIndex's powerful indexing and retrieval capabilities, users can integrate any OpenAI-compatible language model, customize prompt templates, and manage conversation flows via a CLI interface. The modular architecture supports various data connectors, plugin extensions, and dynamic response customization, enabling rapid prototyping of enterprise-grade knowledge assistants, interactive chatbots, and research tools. This solution streamlines building domain-specific AI agents in Python, ensuring scalability, flexibility, and ease of integration.

Ernie Bot Agent is a developer framework designed to streamline the creation of AI-driven conversational agents using Baidu ERNIE Bot. It provides abstractions for API calls, prompt templates, memory management, and tool integration. The SDK supports multi-turn conversations with context awareness, custom workflows for task execution, and a plugin system for domain-specific extensions. With built-in logging, error handling, and configuration options, it reduces boilerplate and enables rapid prototyping of chatbots, virtual assistants, and automation scripts.