AI-Powered Analytics

AI-powered Software Quality Intelligence

Analyze, predict, and improve your code quality in seconds. Get actionable insights powered by machine learning, not guesswork.

Analyze My Project
No setup required
Instant results
Explainable AI
How It Works

Three steps to better code quality

From raw metrics to actionable intelligence in seconds.

01

Input Your Metrics

Enter key data points: commits, bugs, complexity, team size, and test coverage.

02

Get AI Analysis

Our model calculates a quality score, risk level, and confidence rating instantly.

03

Act on Insights

Receive prioritized recommendations and simulate improvements with what-if scenarios.

Who Is This For

Built for teams who ship

Whether you are shipping solo or scaling a team, gain clarity on code health.

Developers

Understand how your commits impact quality. Catch issues before they become tech debt.

  • Personal quality tracking
  • Code impact analysis
  • Optimization tips

Engineering Teams

Align on quality standards across the codebase. Make data-driven engineering decisions.

  • Team benchmarks
  • Historical trends
  • Risk forecasting

Startups

Move fast without breaking things. Balance speed with sustainable code quality.

  • Pre-release checks
  • Technical debt alerts
  • Growth-ready insights
Real-World Example

See it in action

How a growing engineering team used quality intelligence to improve their release cycle.

Case Study

FinFlow: From 40% test coverage to release confidence

A 12-person fintech startup was shipping fast but accumulating technical debt. Bug reports were increasing with each release, and the team had no visibility into which areas of the codebase were at highest risk.

1

Initial Analysis

Score: 52 (High Risk) - Bug density at 0.35, coverage at 40%

2

What-If Simulation

Used simulator to identify: +20% coverage would yield +18 score points

3

Result After 6 Weeks

Score: 78 (Low Risk) - Coverage at 65%, bugs reduced by 45%

Quality Score
78+26

from 52

Risk Level
Low

from High

Test Coverage
65%+25%

from 40%

Bug Reduction
45%

fewer bugs per release

"We finally had visibility into our technical debt. The what-if simulator helped us prioritize the right improvements."

- Engineering Lead, FinFlow

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