Humanloop focuses on enabling users to build, refine, and optimize conversational AI agents. The platform employs feedback loops that facilitate real-time improvements in AI dialogs, ensuring that responses become more relevant and accurate over time. Organizations can leverage Humanloop to enhance customer service, automate responses, and ultimately provide a seamless user experience. By simplifying the training process of AI models, Humanloop empowers teams to focus on refining content rather than wrestling with complex programming tasks.

HumanLayer is an API and SDK that enables AI agents to interact with humans for feedback, approvals, and guidance. By integrating HumanLayer, developers can ensure critical AI decisions are overseen by humans, create custom approval workflows, manage transitions between software- and human-driven processes, and collect valuable human feedback to improve AI systems. It supports integration with popular frameworks and LLMs, making it a versatile tool for various applications requiring human oversight on AI outputs.

OSU NLP Middleware is a lightweight framework built in Python that simplifies the development of AI agent systems. It provides a core agent loop that orchestrates interactions between natural language models and external tool functions defined as plugins. The framework supports popular LLM providers (OpenAI, Hugging Face, etc.), and enables developers to register custom tools for tasks like database queries, document retrieval, web search, mathematical computation, and RESTful API calls. Middleware manages conversation history, handles rate limits, and logs all interactions. It also offers configurable caching and retry policies for improved reliability, making it easy to build intelligent assistants, chatbots, and autonomous workflows with minimal boilerplate code.