A new company is emerging from stealth today with backing from Google's AI-focused venture fund to help businesses compile their open-source AI infrastructure and reduce their engineering overheads.

Cake integrates and secures more than 100 components for enterprises, including data source adapters (e.g. Apache Hadoop), data ingestion (e.g. Apache Kafka), data labelling (e.g. Label Studio), vector and graph databases (e.g. Milvus or Neo4j), generative AI APIs and related tools (e.g. Anthropic), among many other categories.

This hints at why Cake is called what it is -- it takes the various "layers" that constitute the AI stack, and integrates them into a more digestible, production-ready format suitable for business.

On top of its formal unveiling today, Cake said it has raised $13 million since its inception. This includes $3 million in pre-seed funding through its formative couple of years, and a recent $10 million seed round led by Google's Gradient Ventures.

"We haven't been super secretive; we've just been building, and working with customers," Herscu explained to TechCrunch in an interview last week.

Previously, Herscu founded an AI company called McCoy Medical Technologies that was focused on machine learning infrastructure for radiology, and sold it in 2017 to IT vendor TeraRecon. He later joined New York VC firm Primary Venture Partners as "operator in residence," where he pursued his next venture by chatting with hundreds of data science and AI executives.

"I did over 200 customer discovery calls, asking what their biggest pain points and bottlenecks are," Herscu said. "The biggest problem wasn't a single part of the stack, such as setting up a vector database or data pipeline. It was that there are a ton of different components across a very rich ecosystem. How do you go about integrating everything reliably, and making it production ready?"

This is what Herscu refers to as the "big picture problem," and is where his new business enters the fray.

Cake is all about making sense of the myriad open-source components that constitute the modern AI stack, and providing bundled, managed, open-source AI infrastructure for small teams. This isn't about building a business around a single open-source project as countless companies have done; instead, it's about assembling and serving a curated selection of open-source projects across an entire stack and making it run smoothly.