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New research-backed AI ROI methodology for engineering.  Review Whitepaper

An AI ROI number you can stand behind.

Tokens and acceptance rates describe usage, not value. Quotient turns your own engineering data into a dollar figure you can put in front of finance.

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Return on AI Spend Jan – Jun 2026
$0k
Value created
$0k
Total AI spend

Delivered 17% more code 7% faster, while quality held.

YTD (Jan–Jun)
Throughput +17%
Quality +2%
Speed +7%
Data: Quotient
Powering high-performance engineering at:
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Powering high-performance engineering at:
Rho logo
Kargo Logo

Research-backed

A comprehensive picture

Built on current research in AI-assisted development, giving you a complete and trustworthy view of return.

See the research →
All four measures Jan – Jun 2026
Throughput
+0%

The team is shipping more.

Speed
+0%

The team is delivering faster.

Quality
+0%

Quality is holding as output grows.

Developer Experience
+0%

Gains aren’t borrowed from burnout.

Trends over time

Watch it move, quarter to quarter.

The figure updates as your data moves, so you always have an up-to-date view of what AI is returning.

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+0% Throughput

The team is shipping more.

Expected 0PRs
Actual 0PRs
Throughput Gain 0PRs
Actual PRs shipped Expected at baseline pace Extra over baseline

Research-backed

Put the next dollar where it works.

The same engineering data behind your ROI shows where delivery is getting stuck, so you can raise the number instead of only reporting it.

Explore AI Impact →

Bigger AI-driven changes slow flow

AI-assisted output rose sharply and pull request size has grown four months straight. Cycle time has worsened with it — higher output is arriving in batches that move less smoothly.

Batch size
0 ▲0% lines of code per PR
Cycle time
0 ▲0% hours to production
Teams to focus on
Core
Data
Recommended actions
Enforce trunk-based, atomic commit practices for AI-generated code
Case study

Bubble accelerates AI-native development with Quotient

A 51% improvement in AI usage turned into 32% less cycle time and 19% better code quality.

Read the story ->
+51%
AI Usage
-32%
Cycle Time
+19%
Code Quality

See what AI is returning in your org.

71% of CIOs expect their AI budget cut or frozen if they can't show a return by mid-2026. Bring a number you can defend.

Book a Demo
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