Enterprise Kestra orchestration and workflow automation

Stop babysitting fragile pipelines. We design, deploy and scale declarative, event-driven Kestra workflows that connect your data and AI stack, then hand your team a platform they can run.

Book a Discovery Call Compare platforms

Jason, our COO, runs the call. If Kestra is already in your architecture plan, the next step is a scoping session, not another evaluation.

KestraOpen-source orchestration

Licence: Apache 2.0Enterprise Edition is a separate commercial product.
Flows: Declarative YAMLVersioned in Git and promoted from dev to staging to production.
Triggers: Schedules and real-time eventsFile arrivals, message queues and other external events.
Runs on: Docker, Kubernetes, AWS, GCP, AzureYour infrastructure, or on-premises.
Plugins: Hundreds built inDatabases, cloud storage and APIs. We write custom ones where a connector is missing.

From Kestra's GitHub repository and documentation, checked 19 October 2026.

Clients include

Why teams call us

Why enterprise teams struggle to run Kestra alone

Kestra is quick to install and slow to operationalise. The work is in the architecture around it.

Declarative architecture

YAML flows built for reuse, peer review and promotion across environments, under version control from day one.

Event-driven triggers

Webhooks, message queues and database changes that start flows the moment something happens, replacing polling that burns compute and adds lag.

Multi-cloud and hybrid deployment

Kestra on Kubernetes (EKS, GKE or on-premises) with isolated namespaces, encrypted secrets and network policies that clear a security review.

Custom plugins and AI steps

Connectors your stack needs, plus agent steps, LLM validation and human review gates inside the orchestration layer.

A pipeline you can read, review and version

Every Kestra flow is a YAML file. Your engineers review it like code, and analysts can read what it does.

# orders_to_snowflake.ymlid: orders_to_snowflakenamespace: company.sales triggers:  - id: on_new_order    type: io.kestra.plugin.core.trigger.Webhook    key: shopify-orders tasks:  - id: load_orders    type: io.kestra.plugin.jdbc.snowflake.Query    sql: "INSERT INTO raw.orders ..."  - id: review_large_refunds    type: io.kestra.plugin.core.flow.Pause  - id: notify_finance    type: io.kestra.plugin.notifications.slack.SlackIncomingWebhook

What happens on each order

Webhook firesShopify posts the order the moment it is placed. Nothing polls.
Snowflake loadThe order lands in the raw schema for your ELT models.
Person reviewsLarge refunds pause until someone in finance approves them.
Team notifiedFinance gets the result in Slack, and every run is logged in Kestra.

Illustrative flow. Task types are Kestra core and plugin types; your flows are designed in scoping.

Workflows we build on Kestra

Three patterns cover most of what enterprise teams ask for.

Data

Multi-cloud ingestion and ELT

Data from Salesforce and Shopify into Snowflake, started by webhook events instead of scheduled polling windows, so you pay for compute only when there is data to move.

AI content and ingestion pipelines

Vector database updates, fine-tuning runs and content generation, with human review screens as first-class tasks in the flow.

See Forge AI

Operations

Infrastructure alerting and remediation

Cloud resources monitored and recovery flows started when anomalies cross a threshold, so known failures fix themselves without paging your SRE team.

Moving off Airflow or cron?

Most Kestra projects we see start with pipelines that already exist somewhere else.

Airflow DAGsTranslated into declarative YAML, keeping the business logic and dropping the Python operator sprawl.
Scripts and cron jobsBrought under one scheduler with retries, logs and alerts.
n8n workflowsKept where they fit. n8n handles app-to-app automation, Kestra handles the data and AI pipelines behind it.
Git and CIFlows reviewed in pull requests and promoted through dev, staging and production.

In production today

Operational automation we run in production today

A Dutch Odoo implementation partner tried for a year to build scheduling natively for a dental care group. We built five sync workflows and an agent layer on n8n instead. It is not a Kestra build, and it shows how we work: event-driven flows, a person on the exceptions, and the engineers who built it on call.

See all case studies

Dental care groupOdoo and n8n, scheduling

1,500

Appointments scheduled a week

200practitioners

25,000residents served

5sync workflows

How a Kestra implementation runs

Scoping sets the timeline for your workflow, and every build is tested in staging before it goes live. See how we work

AI pilot: 2 to 6 weeks
AI Audit: 4 to 8 weeks
Full build: Set in scoping

Jason, COO
Architecture scoping and environment setup
We audit your data sources, define the security and secrets strategy, and deploy the core Kestra instance with high availability.
- The pipelines to move first
- Where Kestra runs and who can reach it
Maciej, CTO
Pipeline migration and workflow design
We translate legacy scripts or Airflow DAGs into declarative YAML, keeping the business logic intact.
- Flows reviewed in pull requests
- Staging runs against test data
Jason, COO
Integration and event triggers
We wire API connectors, webhooks and real-time listeners across your cloud and on-premises systems.
- Every endpoint connected and tested
- Review gates where people decide
Maciej, CTO
Observability and handover
We set up dashboards, alert thresholds and runbooks, then walk your team through owning the platform day to day.
- Runbooks your team can follow
- Support from the engineers who built it

What teams ask about Kestra orchestration

Ask us something else

Why choose Kestra over Apache Airflow?

Kestra flows are declarative YAML, so engineers and analysts can build and read pipelines without Python dependencies and boilerplate. Kestra is event-driven by design, which suits real-time processing and cloud-native infrastructure better than Airflow's scheduled batches.

How does Kestra handle event-driven orchestration?

Triggers start flows when a webhook arrives, a message lands on a queue or a file appears, instead of polling on a schedule. Pipelines run when events occur, and you stop paying for compute that checks for work that is not there.

Is Kestra open source?

Yes. Kestra is licensed under Apache 2.0. Kestra also sells a separate commercial Enterprise Edition; we build on whichever edition you run.

What does a Kestra implementation partner do?

We set up high-availability infrastructure and secrets management, migrate legacy pipelines, design your flows, build custom plugins and connect Kestra to your data and AI stack, then hand your team an observable, production-ready orchestration layer.

Where should we start?

With the pipeline that breaks most often or costs the most to babysit. Book a discovery call and we scope it with you.

Other platforms we build on

We pick the platform after we understand the workflow, so the same team can build on whichever of these fits it. Compare them all

Workflow automation

n8n

Trigger-and-steps workflows with AI inside them, billed per run and self-hostable in your own cloud.

See n8n

Enterprise AI platforms

Microsoft Foundry

Agents built in your Azure tenant under Entra ID, billed on the Azure account you already have.

See Microsoft Foundry

Simulation and digital twins

Sim AI

Digital twins and simulation runs connected to live R&D and manufacturing data.

See Sim AI

Workplace AI

Claude Cowork

Anthropic's agent for knowledge work, set up with the plugins, connectors and approval steps your teams need.

See Claude Cowork

Workplace AI

ChatGPT for work

ChatGPT rolled out to your company with the connectors, custom GPTs and admin settings it needs.

Page coming

SAP

SAP Joule Studio

Custom Joule skills and agents on SAP BTP, connected to the SAP and non-SAP systems your teams query.

See SAP Joule Studio

Your data stack won't wait for a six-month rollout

If Kestra is already in your architecture plan, the next step is a scoping session. Answer a few questions and Jason sets it up.

Owen, Maciej, Jason, Oskar and Ben