Case Study

How a 32-Person Team Resolved 538 Issues They Would Have Missed

993 pull requests reviewed, 538 issues resolved, $0.10 per review — at 200+ PRs a month.

The Team

A 32-person engineering team building SaaS software, working across 9 active projects in Azure DevOps. The team consistently ships 200+ pull requests per month and uses Azure Boards for work item tracking.

The Challenge

At 200+ PRs per month, the team's human reviewers were doing their best but the sheer volume made it hard to give every PR the same level of scrutiny. The team wanted a way to add a consistent quality baseline to every pull request — an automated first pass that would catch potential issues and let human reviewers focus on architecture, design, and business logic.

The Solution

The team integrated Korekt with Azure DevOps using webhook automation. Every pull request across all projects now receives an automated AI review that checks for potential bugs, security considerations, performance issues, and alignment with Azure Boards work item requirements. Reviews happen automatically — no manual trigger, no changes to the developer workflow.

Results

Over 5 months of production usage:

Active developers 32
Pull requests reviewed 993
Potential issues identified 4,009
Issues resolved by the team 538
Total AI review cost $176
Average cost per review $0.10

The most telling metric: 538 issues resolved. The team isn't just seeing the findings — they're acting on them. That's proof the tool surfaces actionable insights, not noise.

Examples of Issues Caught Early

Korekt catches subtle issues that are difficult to spot in high-volume review environments:

Silent validation bypass

A stored procedure's input parameter was being overwritten by a query result, causing a downstream validation check to always pass — meaning invalid data could flow through undetected.

Hidden error paths

An exception handler was catching database errors but only handling one specific case. All other exceptions were silently swallowed — no logging, no re-throw — meaning real failures would be invisible to monitoring.

Subtle logic inversions

A boolean variable controlling a refresh operation was initialized with inverted logic, causing the exact opposite of the intended behavior under certain conditions.

Data consistency risks

A stored procedure performing multiple sequential updates had no transaction wrapper. If any step failed partway through, the data would be left in a partially modified state.

Actionable Findings, Not Noise

The real test of any code review tool is whether engineers trust it enough to act on the findings. With 538 issues resolved, this team's developers are choosing to address what Korekt surfaces — not dismissing it as false positives. The tool has earned a place in their daily workflow.

The team also uses ticket compliance verification to check whether PRs match Azure Boards work item requirements — catching spec mismatches alongside code quality issues.

"At our scale, consistent review quality across the whole team isn't something you can achieve manually. Korekt gives every PR the same baseline scrutiny, and our engineers trust the findings enough to act on them."

— VP R&D, SaaS Company

This team uses Korekt with Azure DevOps, GitHub, and Azure Boards integration.

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