Announcing Shakudo – the modern data solution I wish I had

One of the things that I both love and hate is the opportunity to set up a new data stack. Each time I think, “this time I’m going to get it right”. And every time without fail, I’m stuck dealing with the tradeoffs of all the options of the “modern data stack”. Simply put:

• it’s too complicated;
• it takes too long;
• it’s too expensive; and
• talent is hard to get.?

I still remember those early days of the COVID response when we were working round the clock to collect data to build and evaluate models, answer basic questions for policy makers, and understand what was taking place in hospitals. We needed a modern data stack fast – I mean within 24 hours fast. We didn’t have time to gather requirements or figure out what technologies play nice with each other. I needed a modern data stack with the push of a button where I could choose different technologies and deploy them without weeks of configuration – just like I can do with iOS or Android and have the apps vetted from their respective stores.?

Fast forward to a few months ago when I was lucky enough to meet Yevgeniy, Stella, and Christine. They knew my pain about complexity, fragmentation, deployment and compatibility challenges of all the technologies available to data engineers and data scientists. And that’s why they started Shakudo – to build the operating system for the modern data stack.?

Shakudo is the fastest/easiest way to build, deploy and manage a best-in-class enterprise caliber data stack. It unites the most widely used data, AI/ML tools and scaling frameworks like DBT, Airflow, Superset, Spark, Ray, Dask and recent tooling in generative AI such as LangChain, ChromaDB, Milvus and leading LLMs into a single platform! And it does so with scalability, compatibility and robustness without an army of data engineers.?

They provide the flexibility to choose the right data tools while solving the compatibility challenges that all too often arise when different teams within an organization try to create their own data stack (e.g., marketing and sales building one custom data stack vs the data stack for the core services). The beauty of Shakudo lies in the fact that a data stack is not a static piece of technology encased in glass but rather a living and evolving system that can be modified or added based on an enterprise's requirement.?

I’m pleased to announce that GPV is leading the Series A round for Shakudo, with participation from existing investors and I’ll be joining the board. Shakudo is central to our thesis at GPV for how the data world is going to evolve. And in particular to be literally the foundation for deploying AI solutions. With their rich blend of leadership roles, technical skills, and industry experience, Yevgeniy Vahlis, Stella Wu, and Christine Yuen are the right team to take on this problem. Their collective expertise in bringing artificial intelligence and data use cases to large scale production through their work in big tech, banking, consulting and growth stage VC signifies a deep comprehension of how advanced technologies can be seamlessly integrated to create efficient and effective data solutions.?

Don’t take my word for it. Go try it for yourself!?

And we’re growing so join us on this exciting journey!