Astral

Astral is an enterprise AI workflow engine that lets you build, deploy, and scale automated processes without writing code. Instead of spending months on internal AI development, teams can drag and drop models from OpenAI, Anthropic, Google Gemini, Deepseek, and others to create agentic workflows. The platform is designed to cut implementation time by up to 90%, making it possible to go from concept to production in days.

The tool works by providing a visual drag-and-drop interface where you connect AI models to your data and business logic. It includes built-in evaluation tools to compare and refine outputs before launch, and it keeps your data private — Astral doesn't use your information to train LLMs. You can also integrate with existing systems (like databases or CRMs) using agentic IDE rules, so developers can hook into your tech stack in minutes. Features like brand voice control, hallucination safeguards, and user permission management give teams confidence in scaling AI use.

Astral is best suited for enterprise teams that want to quickly experiment with AI without waiting on engineering resources. It's particularly useful for marketing, customer success, and content teams looking to personalize at scale — for example, automating personalized email sequences based on customer behavior or generating tailored course feedback. The Gretchen Rubin Media case study on the site shows how the platform helped scale course enrollment from hundreds to thousands while keeping a personal touch.