LLM Stack provides a versatile platform allowing users to deploy AI-driven applications tailored to their specific needs. It offers tools for text generation, coding assistance, and workflow automation, making it suitable for a wide range of industries. Users can create custom AI models that enhance productivity and streamline processes, while seamless integration with existing systems ensures a smooth transition to AI-enabled workflows.

OperAgents is a developer-oriented toolkit for building and orchestrating autonomous agents using large language models like GPT. It supports defining custom agent classes, integrating external tools (APIs, databases, code execution), and managing agent memory for context retention. Through configurable pipelines, agents can perform multi-step tasks—such as research, summarization, and decision support—while dynamically invoking tools and maintaining state. The framework includes modules for monitoring agent performance, handling errors automatically, and scaling agent executions. By abstracting LLM interactions and tool management, OperAgents accelerates the development of AI-driven workflows in domains like automated customer support, data analysis, and content generation.