AI adoption with measurable engineering ROI

Problem

Leadership wants measurable AI impact, but most tools only show individual usage: seats activated, prompts sent, or code suggestions accepted. That does not prove whether the team shipped more, reduced cycle time, or saved engineering capacity.

How it works

Rosvelt measures AI adoption through shipped work: tickets completed, completed work for review opened, previews reviewed, hours saved, cycle time reduced, and agent output across projects.

2Connect the work sources your team already uses: repos, tickets, completed work for review, and reviews.

3Rosvelt tracks the agent lifecycle from request to shipped completed work for review.

4Teams see output by project, work type, agent, and review status.

5Leadership gets evidence of velocity, savings, and adoption based on delivered software.

Threads

Keep product, engineering, QA, and agent decisions attached to the ticket.

What you get

A clearer way to prove AI is changing engineering output — not just increasing tool usage.

Review before you merge

Every metric ties back to real work your team can inspect.

Rosvelt keeps the source of truth connected to tickets, completed work for review, previews, and reviews, so ROI is not a vanity dashboard. Leaders see what shipped, teams see what changed, and engineering keeps final approval over the work.

Preview

Inspect the result, request edits, and move it forward without changing tools.

Why it's different

AI ROI becomes visible in shipped product, not abstract productivity claims.

See it in action

Watch AI adoption turn into measurable engineering outcomes.