LLM State Machine is an open-source Python framework designed to construct AI agents using explicit state machines. Developers define states as discrete steps—each invoking a large language model or custom logic—and transitions based on outputs. This approach provides clarity, maintainability, and robust error handling for multi-step, LLM-powered workflows, such as document processing, conversational bots, or automation pipelines.

Snaplet is a developer tool that provides instant, production-like seed data for your Postgres database. By leveraging AI, Snaplet generates realistic, safe data, allowing developers to code, test, and debug with confidence. The platform ensures data accuracy, removes personal information, and simplifies database setup, thus saving time and enhancing productivity.

Visionari leverages advanced AI technology to streamline the feedback collection and prioritization process for businesses. By gathering user feedback from various channels, analyzing insights with AI, and automating the creation of roadmaps and changelogs, Visionari ensures that companies can efficiently prioritize and implement the most impactful features. This results in increased customer satisfaction and engagement, reducing manual work and enabling a more focused, data-driven approach to product development.

GitGab is a powerful AI-driven tool that integrates advanced AI models such as ChatGPT and Claude with your codebase. It assists developers by automatically implementing new features, identifying and fixing bugs, generating documentation, and optimizing code. By providing contextual understanding and actionable insights, GitGab streamlines the development workflow and improves productivity.

QueryCraft is a Python-based prompt engineering toolkit designed to streamline the development of AI agents. It enables users to define structured prompts through a modular pipeline, connect seamlessly to multiple LLM APIs, and conduct automated evaluations against custom metrics. With built-in logging of token usage and costs, developers can measure performance, compare prompt variations, and identify inefficiencies. QueryCraft also includes debugging tools to inspect model outputs, visualize workflow steps, and benchmark across different models. Its CLI and SDK interfaces allow integration into CI/CD pipelines, supporting rapid iteration and collaboration. By providing a comprehensive environment for prompt design, testing, and optimization, QueryCraft helps teams deliver more accurate, efficient, and cost-effective AI agent solutions.