Mage raises $12M Series A to build 'AI-ready data' and execution layer

What's the deal? Mage has raised a $12M Series A led by SineWave VenturesDealroom has a profile for this one. Try Dealroom →, with participation from Gradient VenturesDealroom has a profile for this one. Try Dealroom →. The company runs a collaborative workspace for data engineering, letting teams build data products and AI applications faster.

What's the endgame? Mage wants to become the execution layer between data, AI, and the people who keep work running. It is building what it calls "AI-ready data" — reusable context covering approved definitions, lineage, freshness, permissions, and operational history.

Why now? Founder Thomas T. Chung argues that a prompt "can sound confident and still be working with incomplete, outdated, or misunderstood information." Mage's pitch: useful AI at work needs trusted context and workflows people can inspect, recover, and govern.

What's the money for? The funding will go toward conversational workflows people can inspect and the wider system underneath what Chung calls "the execution era." The product loop is meant to stay simple: add data, explore data, use data.

The round marks a notable step-up from Mage's previous raise, a signal that investors see momentum behind the company's approach.

The signal: The raise lands as investors chase infrastructure that makes enterprise AI reliable rather than flashy. Mage's bet is that the value sits not in answering questions but in turning answers into governed, recoverable action — a wager that data plumbing, not prompts, decides whether AI earns trust at work.

Read more: m.mage.ai

Image credit: Generated with Gemini