Kestra, the open-source orchestration platform that unifies data pipelines, AI workflows, and infrastructure automation, has closed a 36 million and arrives as the platform executes over 2 billion workflows annually, a 20x increase year over year.
The company's growth tells a story about how enterprise automation is breaking under its own weight. Organizations now run workflows across cloud and on-prem infrastructure, AI agents, real-time data pipelines, and microservices, often stitched together with schedulers and scripts that were never designed for this level of complexity. The result is a familiar one for anyone who has worked in a large engineering organization: silent failures, lengthy compliance reviews, and business-critical logic buried in undocumented scripts.
Kestra's answer is a unified orchestration control plane that is declarative by design, extensible across more than 1,800 plugins, and built for hybrid and air-gapped environments. The platform uses YAML to define workflows, making them version-controllable and reviewable while still accessible through a visual UI for non-engineers.
The customer list reads like a who's who of global enterprises. Apple uses Kestra to orchestrate pipelines between its data warehouse and AI platform. Toyota unified previously siloed data and AI pipelines under a single governed control plane. JPMorgan Chase's security teams process billions of rows through Kestra, triggering automated remediation across platforms. At BHP, the platform replaced a VMware vRA environment across global mining facilities, cutting infrastructure provisioning from six months to six days.
"Most enterprise software companies try to sell top-down and hope developers adopt," said Emmanuel Darras, Kestra's CEO and co-founder. "We inverted that model. Engineers didn't adopt Kestra because we marketed to them. They adopted it because they were frustrated, and Kestra worked."
The funding will accelerate four priorities: the launch of Kestra 2.0 with a new distributed execution engine and native agentic orchestration; Kestra Cloud, a fully managed SaaS offering; expansion of go-to-market operations in North America and Europe; and continued open-source investment in developer experience and the plugin ecosystem.
Kestra's rise also reflects a broader shift in how enterprises think about workflow orchestration. Legacy tools like Apache Airflow, while still dominant, were built for a different era of data engineering. They assume Python-centric teams, scheduled batch jobs, and relatively simple pipeline topologies. Kestra's event-driven architecture, language-agnostic task execution, and built-in UI for building and monitoring workflows address the reality that modern orchestration spans data engineering, infrastructure provisioning, AI model deployment, and business process automation, often within the same organization.
The platform has accumulated 26,000+ GitHub stars and is now the fastest-growing open-source orchestration project by several measures. With the Series A closed and enterprise revenue up 25x since the seed round, Kestra is positioning itself as the default orchestration layer for organizations that have outgrown their current tooling but are not willing to accept the vendor lock-in of proprietary platforms.