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Astronomer, the corporate behind the Apache Airflow-powered information orchestration platform Astro, has secured $93 million in Collection D funding as enterprises more and more search to operationalize AI initiatives via higher administration of their information pipelines.
The funding spherical was led by Bain Capital Ventures, with participation from Salesforce Ventures and present buyers together with Perception, Meritech, and Venrock. Bosch Ventures can also be searching for to take part within the spherical, reflecting industrial curiosity within the know-how.
In an unique interview with VentureBeat, Astronomer CEO Andy Byron defined that the corporate will use the funding to expedite analysis and improvement efforts and increase its world footprint, significantly in Europe, Australia, and New Zealand.
“For us, that is only a step alongside the way in which,” Byron stated. “We wish to construct one thing superior right here. I couldn’t be extra enthusiastic about our enterprise companions, our clients, our product imaginative and prescient, which I believe is tremendous robust in going after collapsing the info ops market.”
How information orchestration grew to become the hidden key to enterprise AI success
The funding targets what {industry} analysts have recognized because the “AI implementation hole” — the numerous technical and organizational hurdles that stop corporations from deploying AI at scale. Knowledge orchestration, the method of automating and coordinating advanced information workflows throughout disparate techniques, has turn out to be a vital part of profitable AI deployments.
Enrique Salem, Companion at Bain Capital Ventures, defined the crucial challenges going through enterprises at this time: “Each firm operates a sprawling, fragmented information ecosystem—utilizing a patchworks of instruments, groups, and workflows that wrestle to ship dependable insights, creating operational bottlenecks and limiting agility. On the coronary heart of this complexity is orchestration—the layer that coordinates all these transferring items.”
Salem famous that regardless of its significance, “at this time’s orchestration panorama is the place cloud infrastructure was 15 years in the past: mission crucial, but fragmented, brittle and sometimes constructed in-house with restricted scalability. Knowledge engineers spend extra time sustaining pipelines than driving innovation. With out strong orchestration, information is unreliable, agility is misplaced, and companies fall behind.”
The corporate’s platform, Astro, is constructed on Apache Airflow, an open-source framework that has seen explosive progress. In line with the corporate’s lately launched State of Airflow 2025 report, which surveyed over 5,000 information practitioners, Airflow was downloaded greater than 324 million occasions in 2024 alone — greater than all earlier years mixed.
“Airflow has established itself because the confirmed de facto commonplace for information pipeline orchestration,” Astronomer CMO Mark Wheeler defined. “Once we take a look at the aggressive panorama within the orchestration layer, Airflow has clearly emerged as the usual answer for transferring fashionable information effectively from supply to vacation spot.”
From invisible plumbing to enterprise AI spine: The evolution of information infrastructure
Astronomer’s progress displays a transformative shift in how enterprises view information orchestration — from hidden backend infrastructure to mission-critical know-how that allows AI initiatives and drives enterprise worth.
“BCV’s perception in Astronomer goes manner again. We invested within the firm’s seed spherical in 2019 and have supported the corporate through the years, now culminating in main their Collection D,” Salem stated. “Past the spectacular progress, Astronomer’s information orchestration has turn out to be much more essential within the age of AI, which requires scalable orchestration and mannequin deployment automation amidst a ballooning sea of information instruments that don’t discuss to one another.”
In line with the corporate’s inside information, 69% of shoppers who’ve used its platform for 2 or extra years are utilizing Airflow for AI and machine studying functions. This adoption charge is considerably greater than the broader Airflow group, suggesting that Astronomer’s managed service accelerates enterprise AI deployments.
The corporate has seen 150% year-over-year progress in its annual recurring income and boasts a 130% internet income retention charge, indicating robust buyer growth.
“Whereas market analysts could also be searching for a transparent winner within the cloud information platforms battle, enterprises have clearly chosen a multi-solution technique—similar to they earlier decided that multi-cloud would far outpace standardization on any single cloud supplier,” Wheeler defined. “Main enterprises refuse to lock right into a single vendor, choosing multi-cloud and various information platform approaches to remain agile and reap the benefits of the most recent improvements.”
Inside Ford’s large AI operation: How petabytes of weekly information energy next-generation automobiles
Main enterprises are already leveraging Astronomer’s platform for classy AI use circumstances that may be difficult to implement with out strong orchestration.
At Ford Motor Firm, Astronomer’s platform powers the corporate’s Superior Driver Help Methods (ADAS) and its multi-million greenback “Mach1ML” machine studying operations platform.
The automotive big processes multiple petabyte of information weekly and runs over 300 parallel workflows, balancing CPU- and GPU-intensive duties for AI mannequin improvement throughout a hybrid public/personal cloud platform. These workflows energy all the pieces from autonomous driving techniques to Ford’s specialised FordLLM platform for giant language fashions.
Ford initially constructed its MLOps platform utilizing Kubeflow for orchestration however encountered important challenges, together with a steep studying curve and tight integration with Google Cloud, which restricted flexibility. After transitioning to Airflow for Mach1ML 2.0, Ford studies dramatically streamlined workflows and seamless integration throughout on-premises, cloud, and hybrid environments.
From AI experiments to manufacturing: How orchestration bridges the implementation divide
A standard problem for enterprises is transferring AI from proof-of-concept to manufacturing. In line with Astronomer’s analysis, organizations that set up robust information orchestration foundations are extra profitable at operationalizing AI.
“As extra enterprises are working ML workflows and real-time AI pipelines, they require scalable orchestration and mannequin deployment automation,” Salem defined. “Astronomer delivers on this at this time, and because the orchestrator, is the one system that sees all the pieces taking place throughout the stack — when information strikes, when transformations run, when fashions are educated.”
Over 85% of Airflow customers surveyed count on a rise in external-facing or revenue-generating options constructed on Airflow within the subsequent yr, highlighting how information orchestration is more and more powering customer-facing functions somewhat than simply inside analytics.
This development is obvious throughout industries, from automotive to authorized know-how corporations which might be constructing specialised AI fashions to automate skilled workflows. These organizations are turning to Astronomer to deal with the advanced orchestration challenges that come up when scaling AI techniques from prototypes to manufacturing environments serving hundreds of customers.
Strategic know-how growth: Airflow 3.0 and cloud partnerships place Astronomer for market management
The corporate lately introduced the final availability of Airflow 3.0, which it describes as “probably the most important launch in Airflow’s historical past.” The replace introduces a number of transformative capabilities designed particularly for AI workloads, together with the flexibility to run duties “anyplace, any time, in any language.”
“Airflow 3.0 lays the muse for executing duties on any machine, on-prem or within the cloud, triggered by occasions throughout the info ecosystem,” Byron defined. “It additionally introduces a proof of idea for outlining duties in languages past Python, tremendously enhancing information workforce agility and facilitating migration from legacy techniques to Airflow.”
Astronomer has additionally expanded its {industry} partnerships, lately reaching the Google Cloud Prepared – BigQuery Designation, making its platform out there for buy instantly from the Google Cloud Market. This permits present Google Cloud clients to expedite their buy of Astro and use their present Google Cloud commit credit.
“We’ve simply signed an superior partnership with IBM,” Byron informed VentureBeat. “They’re placing us into their broader information portfolio of merchandise. And we predict there’s an superior alternative for us, not solely in North America, however internationally, to get a number of momentum with IBM as properly.”
Unified DataOps: The subsequent evolution in enterprise information administration
Salem believes Astronomer is positioned to redefine enterprise information operations, transferring past orchestration to what the corporate calls “unified DataOps” — a complete method integrating observability, high quality administration, and governance right into a single platform.
“We invested in Astronomer in 2019 with a easy wager: Airflow would turn out to be the usual for information orchestration,” Salem stated. “As we speak, it runs at over 80,000 corporations and drives 30 million downloads a month. We backed Astronomer as a result of they’re not solely driving that wave; they’re constructing the enterprise management aircraft on high of it.”
For enterprises struggling to comprehend worth from their AI investments, Astronomer’s progress indicators an important shift in how information infrastructure is constructed and managed — one the place orchestration serves as the muse for the whole information stack.
“As AI raises the stakes for dependable, scalable information infrastructure, we’re doubling down on our funding,” Salem concluded. “Orchestration is simply the beginning. The workforce at Astronomer are poised to unify the whole DataOps stack.”
