Narada AI Assistant is an advanced enterprise automation tool developed by AI experts from UC Berkeley. Unlike traditional AI assistants, Narada's Large Action Models (LAMs) not only generate content but also plan, orchestrate, and execute intricate business processes across various enterprise applications. With integration capabilities for ServiceNow, SAP Concur, Salesforce.com, Slack, and Outlook, Narada simplifies workflows like invoice processing, record updating, approval management, and testing. It converts natural-language instructions into automated tasks, ensuring data privacy and security through on-prem deployment. Narada aims to enhance IT, finance, and operations teams by automating complex workflows.

Skeernir is an open-source AI agent framework designed to accelerate the development of puppet master agents for game automation and process orchestration. The project includes a base template, core APIs, and sample modules that demonstrate how to connect agent logic to target environments, whether simulating gameplay or controlling operating system tasks. Its extensible architecture allows users to implement custom decision-making strategies, plug in machine learning models, and manage agent lifecycles across Windows, Linux, and macOS. With built-in logging and configuration support, Skeernir streamlines testing, debugging, and deployment of autonomous AI agents.

Prometh.ai provides a comprehensive platform for creating autonomous AI agents that can connect to various enterprise systems such as Salesforce, HubSpot, SQL databases, and Zendesk. Users leverage a drag-and-drop interface to define multi-step workflows, set conditional logic, and schedule tasks. Agents can perform a wide range of activities, including generating sales leads, triaging support tickets, generating reports, and conducting market research. The platform’s orchestration core manages concurrent processes and error handling, while built-in analytics dashboards visualize agent performance, enabling continuous optimization.

LinkAgent provides a lightweight microkernel for building AI agents with pluggable components. Users can register language model backends, retrieval modules, and external APIs as tools, then assemble them into workflows using built-in planners and routers. LinkAgent supports memory handlers for context persistence, dynamic tool invocation, and configurable decision logic for complex multi-step reasoning. With minimal code, teams can automate tasks like QA, data extraction, process orchestration, and report generation.