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Oct 2022
Unify orchestration for all engineers. Build, run and govern all your workflows — data, AI, infrastructure, and business — Everything-as-Code, from the UI and with AI.
Kestra is the open-source orchestration platform built to help teams ship faster without losing control—making both scheduled and event-driven automation easy across your entire stack.
Often described as the fastest-growing open-source orchestration platform, Kestra has seen 10x growth year-over-year in adoption and workflow volume.
Everything-as-Code, from the UI: design workflows in the UI (including no-code forms) or in declarative YAML—both stay in sync so automation remains reviewable, auditable, and scalable.
AI-native execution:
• Production AI Copilot generates and refines flows from natural language prompts—while keeping YAML clean and reviewable.
• Agentic orchestration with context: AI Agents combine an LLM with memory (context carried across steps/runs) and tools, so workflows can dynamically choose actions, loop until completion, and adapt to new information.
Built for production teams: extensible integrations, strong execution primitives, and governance—plus automation via API and Terraform for CI/CD at scale.
Experience · 1 entries
All (1)
Investments (1)
2022
Investor
Oct 2022
Unify orchestration for all engineers. Build, run and govern all your workflows — data, AI, infrastructure, and business — Everything-as-Code, from the UI and with AI.
Kestra is the open-source orchestration platform built to help teams ship faster without losing control—making both scheduled and event-driven automation easy across your entire stack.
Often described as the fastest-growing open-source orchestration platform, Kestra has seen 10x growth year-over-year in adoption and workflow volume.
Everything-as-Code, from the UI: design workflows in the UI (including no-code forms) or in declarative YAML—both stay in sync so automation remains reviewable, auditable, and scalable.
AI-native execution:
• Production AI Copilot generates and refines flows from natural language prompts—while keeping YAML clean and reviewable.
• Agentic orchestration with context: AI Agents combine an LLM with memory (context carried across steps/runs) and tools, so workflows can dynamically choose actions, loop until completion, and adapt to new information.
Built for production teams: extensible integrations, strong execution primitives, and governance—plus automation via API and Terraform for CI/CD at scale.