AI
Google's Gradient Ventures Funds Cake's Open-Source AI Platform
2024-12-04
In a significant development today, a fresh company is stepping into the spotlight with the backing of Google's AI-focused venture fund. This company aims to assist businesses in compiling their open-source AI infrastructure and reducing engineering overheads. Cake, the emerging entity, integrates and secures over 100 components crucial for enterprises. These include data source adapters like Apache Hadoop, data ingestion tools such as Apache Kafka, data labelling platforms like Label Studio, vector and graph databases like Milvus or Neo4j, generative AI APIs and related tools like Anthropic, and many more categories. This gives a clear indication of why Cake is named as it is - it takes the diverse "layers" of the AI stack and integrates them into a more manageable and production-ready format suitable for business operations.
Founding and Early Years
Cake was founded in 2022 in New York by Misha Herscu (CEO) and Skyler Thomas (CTO). Last year, it launched and is already collaborating with customers like AI bioscience startup Altis Labs and data intelligence insurtech Ping. However, until now, the company hadn't been making much public noise. Since its inception, Cake has raised $13 million. This includes $3 million in pre-seed funding during its formative years and a recent $10 million seed round led by Google's Gradient Ventures. "We haven't been overly secretive; we've been focused on building and working with customers," Herscu explained in an interview with TechCrunch last week.Previously, Herscu founded McCoy Medical Technologies, an AI company focused on machine learning infrastructure for radiology, which he sold in 2017 to IT vendor TeraRecon. Later, he joined New York VC firm Primary Venture Partners as an "operator in residence" and engaged in extensive customer discovery calls. "I did over 200 customer discovery calls, asking about their biggest pain points and bottlenecks. The main issue wasn't a single part of the stack like setting up a vector database or data pipeline. It was the plethora of different components across a rich ecosystem. How do you integrate everything reliably and make it production-ready?" Herscu said. This "big picture problem" is where his new business comes into play.Cake is all about making sense of the numerous open-source components that make up the modern AI stack and providing bundled, managed open-source AI infrastructure for small teams. It's not about building a business around a single open-source project like many others have done. Instead, it's about assembling and serving a curated selection of open-source projects across the entire stack and ensuring smooth operation.For example, a large financial services company with millions of complex financial data documents might want to perform RAG (retrieval augmented generation) against these files to enhance the quality of natural-language query responses. If an off-the-shelf product doesn't meet the requirements or is not compliant, the company would have to build its own system by installing and integrating multiple different components. Cake can handle this time-consuming task.In another scenario, a hospital might need to build a secure system for analyzing CT scan images, or an e-commerce company might want to upgrade its recommendation engine. These are all potential use-cases for Cake. "We do cover a wide range, but our sweet spot is definitely when companies need more than a simple, off-the-shelf product," Herscu said.Team Expertise and Parallel Development
Cake's CTO Thomas has an extensive background. He previously worked at IBM as a chief architect and more recently was a distinguished engineer and director of strategy at Hewlett Packard Enterprise, which acquired a previous company he worked at called MapR. Thomas has worked on hundreds of projects with both large and small customers and noticed a common trend - almost all of them were using open-source tools in some form, often directly from research labs. Yet, using them in the enterprise wasn't straightforward."It takes a tremendous amount of time for even the largest enterprises to incorporate what's emerging from the labs into their operations," Thomas told TechCrunch. "A lot of it is because much of it isn't ready for enterprise use - it may lack authentication and authorization, and enterprises have to handle these aspects themselves."There are similarities to what Cake is aiming for. In Europe, Finnish Aiven, a $2 billion unicorn, is doing something similar but with a focus on data infrastructure. The most obvious comparison might be Red Hat, which IBM acquired for $34 billion and is renowned for its enterprise-grade Linux operating system (RHEL)."In the early days of Linux, there were thousands of open-source packages that everyone wanted to use but weren't integrated or secure," Thomas said. "There was no proper support model, and that's where the Red Hats of the world made Linux safe for enterprises. We want to do a similar thing for AI today."While there are plans to introduce a hosted version of Cake in the future, for now, companies have to run it in their own environments. For many, this isn't a problem as data privacy regulations prevent them from sending data outside their systems. But a hosted version might be attractive to organizations with lower compliance requirements."It is actually more convenient for us if we can control the cloud," Herscu added.Aside from lead investor Gradient, Cake's seed round saw participation from its pre-seed investor Primary Venture Partners, as well as Alumni Ventures, Friends & Family Capital, Correlation Ventures, and Firestreak Ventures. The previously unannounced $10 million seed round, which closed in April, not only reflects the founders' backgrounds but also the company's progress. Herscu said the company is already looking towards its next financing round, with tentative plans to raise again around the middle of 2025. "From a traction perspective, we already look like a Series A company. We were able to achieve this relatively quickly. When we go for the Series A, it might seem more like a Series B," Herscu said.