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Description

Blitzy is an innovative platform powered by artificial intelligence that aims to enhance the speed of enterprise software development by automating as much as 80% of the entire process. Employing a network of over 3,000 specialized AI agents, Blitzy is capable of thinking, planning, building, and validating code according to specified technical requirements. The platform can handle massive codebases of up to 100 million lines seamlessly, ensuring comprehensive awareness of projects and resolving issues related to fragmentation. Additionally, Blitzy's AI agents work together to create detailed technical documentation, outline changes in simple language, and generate high-quality, enterprise-level code at scale, capable of delivering as much as 3 million lines in a single execution, complete with integrated quality assurance measures. It is versatile enough to support both the development of new products and enhancements to existing ones, enabling users to easily link their code repositories, access the latest documentation, and implement additional features or code refactoring as needed. This robust functionality positions Blitzy as a transformative tool for organizations seeking to streamline their software development efforts.

Description

RA.Aid is an open-source AI assistant that streamlines research, planning, and execution to accelerate software development workflows. Utilizing LangGraph's agent-based task management structure, RA.Aid functions through a three-tier architecture. It is compatible with various AI providers, such as Anthropic's Claude, OpenAI, OpenRouter, and Gemini, giving users the flexibility to choose models that align with their specific needs. Furthermore, the assistant incorporates web research functionalities, allowing it to gather current information from the internet to improve its task performance and understanding. Users can engage with the agent through an interactive chat mode, which makes it easy to pose questions or redirect tasks as desired. In addition, RA.Aid can work in conjunction with 'aider' by using the '--use-aider' command, which enhances its code editing capabilities. It is also equipped with a human-in-the-loop feature, allowing the agent to request user input during task execution to achieve greater precision. By combining automation with human oversight, RA.Aid aims to create a more effective development experience for users.