Serverless data platform startup Bauplan Inc. wants to help software developers automate their big data infrastructure with code after raising $7.5 million in seed funding today.
The round was led by Innovation Endeavors and saw participation from angel investors such as the renowned software developers Wes McKinney and Aditya Agarwal, plus the data scientist Chris Re.
The startup has developed a “serverless runtime” that’s uniquely able to process large object storage-based datasets using commands written in the Python programming language. It enables developers to build powerful applications, including artificial intelligence-based apps, by using simple Python functions and familiar Git-style concepts such as branch, commit and merge.
With Bauplan, developers can use Python functions to spin up large-scale data pipelines and gits-for-data across any S3-compatible data lake. It handles the manual infrastructure tasks that would traditionally be performed by experienced data scientists or engineers, helping developers teams run large-scale machine learning workflows, AI applications and data transformation pipelines in the cloud without worrying about the data backend.
In a nutshell, Bauplan is trying to do for data what “serverless computing” and “infrastructure-as-code” did for cloud-based infrastructure when the concepts first arose a few years back. The goal is to eliminate the complex, manual work associated with setting up and configuring data infrastructure such as Kubernetes and Spark, so developers can focus on building their applications, providing them with the data they need without putting any thought into how it’s delivered.
Constellation Research Inc. analyst Holger Mueller said Bauplan is looking to solve a major headache for developers. “Infrastructure has always been the nemesis of developer productivity, slowing them down by keeping them from working on what they’re meant to be doing, which is writing code,” he said. “The data infrastructure for AI is especially complex due to its open-source legacy.”
Bauplan said the main impediment with data infrastructure management is that it involves piecing together dozens of complex platforms that can only be managed by specialists, limiting data-intensive operations to skilled professionals. As a result, developer teams are often forced to ask for help, or else spend days trying to work things out for themselves, slowing down innovation to a crawl.
It’s for this reason that the startup aims to make data infrastructure accessible to software developers, providing them with a code-first approach that can integrate with their continuous integration/continuous development workflows. Its platform is based on Python, one of the most popular and widely known programming languages, in order to free developers from the need to learn Spark or Structured Query Language.
Bauplan co-founder and Chief Executive Ciro Greco (pictured, center, alongside co-founders Jacopo Tagliabue and Mattia Pavoni) said today’s data landscape looks a lot like the DevOps world did 10 years ago.
“Back then, infrastructure-as-code allowed all kinds of developers to automate a lot of stuff, and data is now going through the same process today,” Greco said. “We had a revelatory moment at the beginning of this year when a large infrastructure team put the system in production and we went from zero to 40,000 jobs per week.”
Michael Ni of Constellation Research told SiliconANGLE that with enterprises now scaling AI and data analytics to aid in critical business decision-making processes, one of the next frontiers is applying established software engineering discipline to data pipelines.
“Bauplan’s code-first, serverless platform reflect the convergence of data trust and data-as-a-product thinking,” Ni said. “By removing the complexity of Spark and Kubernetes, it enables developers to build and deploy AI applications through Python-native workflows, accelerating delivery wile ensuring governance and repeatability.”
Bauplan said its platform is designed for medium-to-large enterprises working on data-intensive applications in industries such as financial services, healthcare, business-to-business software and media. One of its early adopters is the Dutch media and communications firm MFE – MediaForEurope N.V., which is focused on free-to-air and pay-TV production and distribution across multiple content platforms.
As a media organization dealing with thousands of different types of content and dozens of distribution platforms, MFE-MediaForEurope has long been accustomed to dealing with data infrastructure-related headaches, said Fabio Melen, the company’s head of data technology. By adopting Bauplan, it has found the ultimate migraine relief.
“Developers who have the expertise to work on data can now focus on the actual work and never deal with infrastructure,” Melen said. “At the same time, developers who are green or have a traditional backend and software engineering background can now build production-grade solutions with data.”
Innovation Endeavors Partner Davis Treybig said Bauplan has created a Lambda-like experience for the most complex data and AI workloads.
“By removing all the infrastructure complexity and abstraction overhead of tools like Spark, they allow any software engineer to be a data engineer,” he explained. “This is an essential shift as all companies become AI-driven.”
Photo: Bauplan
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