Cleo vs Linear: which is the right AI product engineer for your team?
Cleois an AI product engineer that runs the product loop continuously: listen across customer sources, turn signal into sourced bets, hand them to your coding agents with the full context, then prove the impact with honest deltas. A human makes the call on a weekly rhythm. Here’s how that compares to Linear in practice.
Side-by-side
When Linear is the right call
Any product team that needs a tracker. Linear is the execution surface where engineers actually work: cycles, projects, issues, sub-issues, triage.
When Cleo is the right call
Teams that already use a tracker (often Linear itself) but lack the layer above it: synthesizing customer signal into what to put in the tracker in the first place, and measuring what happened after.
Frequently asked
Does Cleo replace Linear?
No. Cleo sits above your tracker, not in place of it. Most Cleo customers use Linear (or Jira) for execution. Cleo decides what should become an issue and drafts it; Linear is where the engineering work actually happens.
Does Cleo integrate with Linear?
Yes. When Cleo recommends shipping, it can create the Linear issue with the spec attached and source signals linked, so your engineers open the ticket and already know why it exists.
Can I migrate from Linear to Cleo?
There's nothing to migrate. They do different jobs. Keep Linear as your tracker and add Cleo as the layer that decides what enters the tracker and measures what happened after.
How does pricing compare?
Linear is per-user (Standard $8/user/mo, Plus $14/user/mo). Cleo is priced as a flat workspace fee, not per maker. They stack. Most teams pay for both because they're complementary.
Why not just use Linear's project docs and call it product management?
Linear is excellent at execution. The gap it doesn't fill is upstream: synthesizing scattered customer signals into a sourced decision and tracking downstream impact. That's the loop Cleo runs.
See Cleo run on your data. Book a 30-min walkthrough.
We’ll plug Cleo into your real customer signal (or a sample dataset) and run a week of the loop live, side-by-side with whatever you use today.
Book a walkthrough →