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Astronomerthe corporate behind the Apache Airflow-powered knowledge orchestration platform Astro, has secured $93 million in Collection D funding as enterprises more and more search to operationalize AI initiatives by way of higher administration of their knowledge pipelines.
The funding spherical was led by Bain Capital Ventureswith participation from Salesforce Ventures and current buyers together with Perception, Meritechand Venrock. Bosch Ventures can also be looking for to take part within the spherical, reflecting industrial curiosity within the expertise.
In an unique interview with VentureBeat, Astronomer CEO Andy Byron defined that the corporate will use the funding to expedite analysis and growth efforts and increase its world footprint, notably in Europe, Australia, and New Zealand.
“For us, that is only a step alongside the best way,” Byron stated. “We wish to construct one thing superior right here. I couldn’t be extra enthusiastic about our enterprise companions, our prospects, our product imaginative and prescient, which I believe is tremendous sturdy in going after collapsing the info ops market.”
How knowledge orchestration turned 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 knowledge workflows throughout disparate methods, has grow to be an integral part of profitable AI deployments.
Enrique SalemAssociate at Bain Capital Ventures, defined the important challenges dealing with enterprises immediately: “Each firm operates a sprawling, fragmented knowledge ecosystem—utilizing a patchworks of instruments, groups, and workflows that battle 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 shifting items.”
Salem famous that regardless of its significance, “immediately’s orchestration panorama is the place cloud infrastructure was 15 years in the past: mission important, but fragmented, brittle and sometimes constructed in-house with restricted scalability. Knowledge engineers spend extra time sustaining pipelines than driving innovation. With out sturdy orchestration, knowledge is unreliable, agility is misplaced, and companies fall behind.”
The corporate’s platform, Astrois constructed on Apache Airflow, an open-source framework that has seen explosive development. In response to the corporate’s lately launched State of Airflow 2025 reportwhich surveyed over 5,000 knowledge practitioners, Airflow was downloaded greater than 324 million instances in 2024 alone — greater than all earlier years mixed.
“Airflow has established itself because the confirmed de facto customary for knowledge pipeline orchestration,” Astronomer SVP of Advertising Mark Wheeler defined. “Once we take a look at the aggressive panorama within the orchestration layer, Airflow has clearly emerged as the usual resolution for shifting trendy knowledge effectively from supply to vacation spot.”
From invisible plumbing to enterprise AI spine: The evolution of information infrastructure
Astronomer’s development displays a transformative shift in how enterprises view knowledge orchestration — from hidden backend infrastructure to mission-critical expertise that permits 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 development, Astronomer’s knowledge orchestration has grow to be much more necessary 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 response to the corporate’s inside knowledge, 69% of shoppers who’ve used its platform for 2 or extra years are utilizing Airflow for AI and machine studying functions. This adoption fee is considerably larger than the broader Airflow group, suggesting that Astronomer’s managed service accelerates enterprise AI deployments.
The corporate has seen 150% year-over-year development in Astro (managed SaaS platform) annual recurring income and boasts a 130% internet income retention fee, indicating sturdy buyer enlargement.
“Whereas market analysts could also be on the lookout for a transparent winner within the cloud knowledge platforms battle, enterprises have clearly chosen a multi-solution technique—identical 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 knowledge platform approaches to remain agile and benefit from the most recent improvements.”
Inside Ford’s huge AI operation: How petabytes of weekly knowledge energy next-generation autos
Main enterprises are already leveraging Astronomer’s platform for classy AI use circumstances that will be difficult to implement with out sturdy orchestration.
At Ford Motor FirmAstronomer’s platform powers the corporate’s Superior Driver Help Techniques (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 growth throughout a hybrid public/non-public cloud platform. These workflows energy the whole lot from autonomous driving methods to Ford’s specialised FordLLM platform for big language fashions.
Ford initially constructed its MLOps platform utilizing Kubeflow for orchestration however encountered vital challenges, together with a steep studying curve and tight integration with Google Cloudwhich restricted flexibility. After transitioning to Airflow for Mach1ML 2.0, Ford stories 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 typical problem for enterprises is shifting AI from proof-of-concept to manufacturing. In response to Astronomer’s analysis, organizations that set up sturdy knowledge 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 immediately, and because the orchestrator, is the one system that sees the whole lot occurring throughout the stack — when knowledge strikes, when transformations run, when fashions are skilled.”
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 knowledge orchestration is more and more powering customer-facing functions relatively than simply inside analytics.
This development is obvious throughout industries, from automotive to authorized expertise corporations which can 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 methods from prototypes to manufacturing environments serving hundreds of customers.
Strategic expertise enlargement: Airflow 3.0 and cloud partnerships place Astronomer for market management
The corporate lately introduced the overall availability of Airflow 3.0which it describes as “essentially the most vital 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 bettering knowledge group agility and facilitating migration from legacy methods to Airflow.”
Astronomer has additionally expanded its {industry} partnerships, lately attaining the Google Cloud Prepared – BigQuery Designation, making its platform out there for buy immediately from the Google Cloud Market. This enables current Google Cloud prospects to expedite their buy of Astro and use their current Google Cloud commit credit.
“We’ve simply signed an superior partnership with IBM,” Byron instructed VentureBeat. “They’re placing us into their broader knowledge portfolio of merchandise. And we expect there’s an superior alternative for us, not solely in North America, however internationally, to get quite a lot of momentum with IBM as properly.”
Unified DataOps: The following evolution in enterprise knowledge administration
Salem believes Astronomer is positioned to redefine enterprise knowledge operations, shifting 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 grow to be the usual for knowledge orchestration,” Salem stated. “In the present day, 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 airplane on prime of it.”
For enterprises struggling to understand worth from their AI investments, Astronomer’s development alerts a vital shift in how knowledge infrastructure is constructed and managed — one the place orchestration serves as the muse for your entire knowledge stack.
“As AI raises the stakes for dependable, scalable knowledge infrastructure, we’re doubling down on our funding,” Salem concluded. “Orchestration is simply the beginning. The group at Astronomer are poised to unify your entire DataOps stack.”
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