e-volv launches on Product Hunt later today. It is a control plane for the SDLC: draw a workflow on a canvas, and agents run it across GitHub, GitLab, Bitbucket, Azure DevOps, Jira, Linear and ClickUp review PRs, triage issues, break down tickets, write changelogs, gate releases. 88 playbooks ship with it, ready to run.
The design we are proudest of is control. Approval gates hold a run until a person decides. Agents hold only the tools you hand them. Your own model keys, your own spend. Every step, every tool call and every token is recorded and replayable.
So, a question for this forum: where does a human add the most value once agents handle the routine work?
Agent opens the PR, you review it like anyone else's
Agent comments, a person makes the change
Agent merges behind a gate for a named class of change dependency bumps, changelogs, release notes
Draw a workflow, and agents run it across your whole pipeline: review PRs, triage issues, break down tickets, write changelogs, gate releases. Works across GitHub, GitLab, Jira, Linear and ClickUp. Your model keys, your spend, human approval where you want it.
