Financing led by NEA will fuel growth and development for the open source Flyte platform, allowing users to scale and optimize AI and ML applications

Union.ai, provider of the open source workflow orchestration platform Flyte, today announced they have closed $10 million in seed funding led by NEA with additional participation from a select group of angels to accelerate the growth of Flyte and provide even greater assistance to its user community. The investment will be used to further grow the Flyte open source ecosystem while building out a commercially available Union Cloud platform.

Machine learning (ML) has the potential for explosive impact across all industries. Existing tooling has not caught up to modern ML requirements, including reliability, reproducibility, enforcement of quality and efficiency. This undermines the efficacy of the models and reduces potential ROI.

“The requirements for ML/Data are very different from delivering services to production,” said Ketan Umare, CEO at Union.ai. “ML/Data workflows are focused on experimentation and are stateful. Meanwhile, dealing with infrastructure procurement is one of the last things a data scientist wants to do. With Flyte, we are solving common issues for running ML workflows, including separating the concerns of infrastructure management from the end user, providing guaranteed reproducibility (a common requirement for deploying complex ML and data applications) and allowing organization-wide re-use of existing applications. As a software engineer, I do not remember the last time I wrote a sorting algorithm, but in the world of ML and Data, redoing the same thing over and over again is the norm. We want to change that.”

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With Union.ai, engineers and data scientists can abstract away the complexity behind workflow automation and focus solely on developing models to solve their core business problems. Union.ai offers new services on top of Flyte so that users can integrate with state of the art machine learning tools, develop reproducible and shareable models, and reap the benefits of a thriving open source, serverless platform.

“When we started thinking about how we could further help the community, we realized that offering a hosted solution where users could get up and running in minutes would help improve their velocity,” added Ketan. “Many teams expressed they were reluctant to embark on hosting Flyte on their own. We want to reassure them that we’re like ‘Flyte’ attendants, here to help them every step of the way through a cloud offering that allows them to start building production-grade ML pipelines in minutes.”

Flyte originated at Lyft, where the founders were trying to solve their own problems to continuously deliver robust machine learning models. Rapid adoption within the company led to Flyte driving most business-critical workloads. Lyft then decided to open source the technology so that they could collaborate with others facing similar challenges. The technology has since been adopted by Spotify and other leading technology companies.

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“NEA has deep experience investing in open source platforms, and we get excited when we find something gaining so much traction within the community,” said Greg Papadopoulos, PhD, Venture Partner at NEA. “In developing Flyte, the Union.ai team has demonstrated tremendous user-first focus on ‘Productionization,’ reliability and streamlining the journey to build complex data and ML applications—which has resulted in a hugely enthusiastic community. We are thrilled to partner with Ketan, George and the team to pioneer the future of data and machine learning orchestration.”

“We built Flyte with the goal of revolutionizing ML pipelines to help ML and data engineers to easily author robust and reusable pipelines,” said Union.ai CTO Haytham Abuelfutuh. “At Union.ai, we are building the Union Cloud platform, which intends to make Flyte accessible to teams across all industries. We offer a low-overhead, secure, enterprise-grade, scalable and performant environment to collaborate on and execute Flyte workflows–all while keeping sensitive data and code within our customers’ control.”