BrainX is a PHP-based AI agent platform designed to simplify the creation and orchestration of intelligent chatbots and assistants. It offers unified interfaces to integrate multiple language models (OpenAI, Azure, etc.), combined with flexible memory drivers to preserve conversation context across sessions. Prebuilt connectors enable deployment on Slack, Telegram, and other messaging channels. Developers can configure prompt templates, response handling pipelines, and caching strategies to optimize performance and user experience. With its modular architecture, BrainX makes it easy to extend functionality, manage sessions, and monitor interactions in production-grade AI applications.

Serverless AI Agent simplifies the creation and deployment of autonomous AI agents by leveraging serverless cloud functions. By defining agent behaviors in simple configuration files, developers can enable AI-driven workflows that process natural language input, interact with APIs, execute database queries, and emit events. The framework abstracts infrastructure concerns, automatically scaling agent functions in response to demand. With built-in state persistence, logging, and error handling, Serverless AI Agent supports reliable long-running tasks, scheduled jobs, and event-driven automations. Developers can integrate custom middleware, choose from multiple cloud providers, and extend the agent’s capabilities with plugins for monitoring, authentication, and data storage. This results in rapid prototyping and deployment of robust AI-powered solutions.

Spider Clients are lightweight, language-specific SDKs that communicate with a Spider orchestration server to coordinate AI agent tasks. Using HTTP requests, clients enable users to open interactive sessions, dispatch multi-step chains, register custom tools, and retrieve streaming AI responses in real time. They handle authentication, serialization of prompt templates, and error recovery under the hood, while maintaining consistent APIs across Node.js and Python. Developers can configure retry policies, log metadata, and integrate custom middleware to intercept requests. The CLI client supports quick testing and workflow prototyping the terminal. Together, these clients accelerate the development of AI-powered agents by abstracting low-level network and protocol details, allowing teams to focus on prompt design and logic orchestration.

Tongui Agent provides a modular architecture for creating AI agents that can maintain conversation state, leverage external tools, and coordinate multiple sub-agents. Developers configure LLM backends, define custom actions, and attach memory modules to store context. The framework includes an SDK, CLI, and middleware hooks for observability, making it easy to integrate into web or Node.js applications. Supported LLMs include OpenAI, Azure OpenAI, and open-source models.