AuroraML debuts 'Aurora Flow' low-code model builder and raises $65M

AI · 5 min read

AuroraML today unveiled Aurora Flow, a drag-and-drop environment that lets non-expert product teams assemble pretrained vision, language, and speech components into deployable pipelines. Flow emphasizes explainability and UI-focused outputs, giving designers control over prompt templates and output scaffolding.

The company also closed a $65 million Series C led by Meridian Capital, which will fund GTM expansion, managed inference infrastructure, and a new partnership program with UX consultancies. Customers will be able to deploy Flow pipelines on a managed stack or export reproducible Docker artifacts for on-prem hosting.

AuroraML positions Flow as an alternative to building custom models from scratch and as a bridge to full MLOps for teams that need faster iteration. Early adopters include healthcare and retail design teams using Flow to prototype multimodal chat assistants that return structured UI components.