Objective Analysis
Every piece of code is evaluated against the same standard criteria; quality swings tied to subjective comments disappear.
Code Review | BGTS
Code Review scans pull requests and commits with AI; classifies findings, delivers a prioritized action plan to developers, and makes merge decisions data-driven.
Analyze every code change against objective criteria in seconds; make quality measurable and catch critical risks before release.
Every piece of code is evaluated against the same standard criteria; quality swings tied to subjective comments disappear.
Quality score, automatic summary, and clear merge recommendation accelerate decision-making.
Production risks such as SQL injection, blocking I/O, and thread safety are blocked before release.
Major and minor issues are separated; line-by-line actionable suggestions and positive highlights are provided.
Traditional code review processes reduce team velocity, fail to maintain consistent standards, and make it impossible to track project-wide quality numerically.
Manual review processes take hours and reduce sprint speed.
Code quality depends on the reviewer's current perspective and experience; standards cannot be maintained.
Code quality and progress across the project cannot be tracked numerically.
When a commit or pull request is submitted, static analysis and AI review kick in; findings are classified, and after developer approval a merge or report is produced.
The developer submits a code change as a pull request or commit.
Code structure, patterns, and known anti-patterns are scanned automatically.
Central review engine — AI analysis, classification, and reporting orchestration.
AI evaluates code against objective criteria; produces critical, major, and minor findings.
Critical risks, important issues, minor improvements, and positive highlights are separated.
Prioritized action items are presented to the developer; approval follows completed fixes.
Merge decision or detailed review report is produced with quality score and merge recommendation.
End-to-end review experience — from standard criteria to line-by-line suggestions, quality scores to prioritized action plans.
AI analyzes every piece of code against the same objective criteria within seconds.
Speeds up the review process and creates a pre-filter for code before human review.
Generates an automatic summary, quality score, and clear merge recommendation for every code change.
Prevents issues that would crash production, such as SQL injection, blocking I/O, and thread safety.
Separates important issues from minor improvements; details architectural debt and test gaps.
Highlights quality code examples such as clear docstrings, modular functions, and type hints.
Does not leave issues general; points out exactly which lines they are in and suggests applicable fixes.
Converts all review results into prioritized clear items; clarifies what the developer should fix and in what order.
Scattered code fragments pass through the AI filter and are classified against standard criteria.

Quality score and merge recommendation clarify decision processes.

Critical issues that must be fixed are detected instantly and presented with detailed explanations.

Makes technical assessment visible by separating major and minor issues.

AI doesn't just look for errors; it also highlights well-written code.

Exact line references and instantly applicable solution suggestions for every issue.

All review results are converted into clear, prioritized checklist items.
