Drive Flow is a flexible framework that empowers developers to design AI-powered workflows by defining sequences of steps. Each step can invoke large language models, execute custom functions, or interact with persistent memory stored in MemoDB. The framework supports complex branching logic, loops, parallel task execution, and dynamic input handling. Built in TypeScript, it uses a declarative DSL to specify flows, enabling clear separation of orchestration logic. Drive Flow also provides built-in error handling, retry strategies, execution context tracking, and extensive logging. Core use cases include AI assistants, automated document processing, customer support automation, and multi-step decision systems. By abstracting orchestration, Drive Flow accelerates development and simplifies maintenance of AI applications.

Par GPT provides a simple interface to dispatch large volumes of OpenAI GPT calls in parallel, optimizing API usage and reducing end-to-end latency. Developers define prompt tasks, and Par GPT automatically manages subprocess workers, enforces rate limits, retries failed requests, and consolidates outputs into structured results. It supports customization of worker counts, timeouts, and concurrency controls across Windows, macOS, and Linux platforms.