Type it, done.
Create any automation by describing it in plain language. No flowcharts, no drag-and-drop wiring, no developer required.
Connect Control D and Jira — AI-native workflow automation
Build multi-step AI automations that flow through Control D and Jira — and chain in 1000+ other apps when the workflow needs them. One instruction, many steps, every API call run by AI. No code, no flowcharts, self-healing.
Control D and Jira are two anchors of a much bigger automation. Definable Workflow chains your dev workflow, your project tracker, and as many other tools as the job needs into a single multi-step flow — built, executed, and verified by AI. Describe the outcome; Workflow plans the steps, runs every API call, branches on conditions, fans out in parallel where useful, retries on failure, and self-heals when an upstream API shifts shape.
What you can automate between Control D and Jira
6 ways to automate Control D + Jira
- When a pull request opens in Control D, create a task with full context in Jira
- When a build fails in Control D, move the task to a new column in Jira
- When a new task is created in Jira, file a tracked issue in Control D
- When a task status changes in Jira, post a status update in Control D
- When a new issue is filed in Control D, assign the right owner in Jira, and log the result in a structured record for team review
- When a deploy completes in Control D, attach a comment with the latest update in Jira, then send a notification to the assigned owner with the full context
Most automation tools run code. Workflow runs on AI.
AI builds it AND runs it.
Other platforms use AI to generate brittle code that runs offline. Workflow's entire execution layer is AI — it interprets, decides, and acts step by step.
Self-healing by design.
Every step is monitored by a verification layer. If something fails — a rate limit, an unexpected response, a skipped condition — Workflow detects it, corrects it, and reruns automatically.
Cross-tool orchestration.
Multi-step, event-driven, condition-based flows across Control D, Jira, and 1000+ other tools — all from one instruction.
How Definable Workflow automation works — step by step
- 1
Describe your workflow
Type what you want to happen between Control D and Jira. No setup wizard.
- 2
Workflow builds it automatically
Definable maps your instruction to the right actions across both tools. You see the plan before it runs.
- 3
AI executes every step
Workflow runs end-to-end. It calls Control D, processes the data, applies your conditions, and fires the Jira action.
- 4
The verification layer monitors everything
Every step is verified. If something fails, Workflow catches it, adjusts, and retries — without you lifting a finger.
Example workflow
Trigger
When delete device by id in Control D
Condition
If the Control D event matches your configured filter
Action
Bulk Create Issues in Jira
Verified
Workflow verified all steps completed successfully.
Frequently asked questions
What can I automate between Control D and Jira?
Anything you can describe. Workflow connects Control D (your dev workflow) and Jira (your project tracker) through a single instruction. Examples: when a pull request opens in Control D, create a task with full context in Jira; when a build fails in Control D, move the task to a new column in Jira. There's no limit to step count or branching depth.
Do I need to write code to connect Control D and Jira?
No. You describe the outcome in plain language and Workflow assembles the steps, authenticates both tools, runs the flow end-to-end, and self-corrects if anything fails.
What happens if Control D or Jira returns an unexpected response?
Workflow has a verification layer on every step. If a response is malformed, an API rate-limit hits, or a condition is unmet, Workflow detects it, adjusts, and reruns the step automatically — without breaking the flow.
How is this different from drag-and-drop automation tools?
Most automation tools generate static workflows that run brittle code. Workflow is AI-native: the execution layer interprets each step at runtime, so it adapts when Control D ships an API change or Jira returns a new field shape. You don't maintain it.
How long does it take to set up?
Minutes. Authenticate Control D and Jira, type what you want to happen, review the plan Workflow generates, and start running.
Your workflows. Built by AI. Run by AI. Fixed by AI.
Stop maintaining automations. Start describing outcomes. Workflow handles everything between Control D, Jira, and your entire stack.