Engineering orgs use Quotient to reduce agent friction, optimize team outcomes, and prove AI is improving delivery.
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Quotient measures how AI and agents change delivery, ranks what's actually slowing your teams, and gives you the specific actions to take next.
After each task, Quotient identifies and fixes agent friction using solutions from across the team.
Correlate AI adoption with delivery outcomes, and get research-backed actions based on the bottlenecks Quotient identifies.
| BY TEAM | AI USAGE | EFFECTIVENESS |
|---|---|---|
| Core API | +51% | +24% |
| Platform | +42% | +18% |
| Payments | +38% | +2% |
Quotient turns your engineering data into a dollar figure you can defend and make decisions on.
How it works
Move from incomplete information to measurable change, for your teams and their agents.
Bubble
Our teams now have a unified view of where AI is paying off, a clear plan to push it further, and tools to measure whether each experiment worked. That loop is what AI-native engineering actually looks like in practice.
Rho
AI moves fast. What matters is knowing what's helping versus getting in the way. That clarity we get from Quotient tells us where to lean in, where to train, and where to stop forcing it.
Kargo
Instead of focusing on fixing the data, we now focus on fixing problems that matter to the team, and that has allowed us to become a more efficient and productive group.
Why Quotient
Quotient's analysis and recommendations are powered by the latest research on AI impact and developer productivity.
Quotient ties each insight to a set of actions to remediate and the signals to track impact. For agents, the fix itself.
Quotient treats engineers and their agents as one team, and measures and improves both.
Connect the systems your teams already use to get a ranked view of what is holding delivery back. Add Agent Experience to fix what slows down their agents.