Linear

In Karumi

Turn Karumi session follow-ups into tasks in Linear and share your Karumi where your team works.

Keep Linear in sync with what happens in every Karumi session.

Follow-ups from a conversation shouldn’t live in someone’s memory. The integration sends session outcomes and the details visitors share to Linear, so the next step is assigned, visible and easy to act on.

How this integration supercharges your workspace:

  • Follow-up tasks

    Turn follow-ups from a session into tasks in Linear, assigned to whoever owns the next step.

  • Form data capture

    Pass the details visitors share in a session, like the email they leave to start a demo, to Linear.

  • Embedded Karumi

    Open your Karumi right inside Linear, where your team already works, without switching tools.

See Linear data in Karumi

Get complete context on who you’re chatting with in real-time

Use cases

  • Turn session follow-ups into tasks

    Create and update tasks in Linear from sessions, so every next step has an owner.

  • Share where your team plans

    Embed and share directly in Linear, next to the projects it relates to.

  • Collect form data with the task

    Details submitted in forms can be sent to Linear along with the task.

Data that flows between Karumi and Linear

DataWhat it is
Tasks Tasks created or updated in Linear
Form data Details submitted during a session
Embeds Shared content opened directly in Linear

FAQ

What does Karumi do in Linear?

Karumi creates and updates tasks, sends data collected in forms, and lets you embed and share directly in Linear.

Do I need engineering to connect Linear?

No engineering on your side: Karumi’s rollout is live in two weeks. Talk to sales to go through how Linear fits into your setup.

Is my data secure?

Karumi is GDPR compliant, and the Enterprise plan includes SOC 2 Type II and ISO 27001. With scoped actions, you define what the agent can see, say and do, per audience.

Is session data used to train AI models?

No. Your data stays yours: session recordings, transcripts and visitor inputs are never used to train models.

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