LetMeCheck.ai

Product Introduction

1. LetMeCheck.ai is a code quality analysis platform that provides actionable insights into codebase health, focusing on scalability, performance, and security issues. It integrates with GitHub repositories to perform automated scans using industry-standard tools and AI-powered analysis. The platform delivers prioritized recommendations through a severity dashboard and offers ready-to-implement fixes for detected issues.
2. The core value of LetMeCheck.ai lies in its ability to help technical leaders make informed decisions about code quality before critical business events. By combining automated Git-triggered scans with AI-generated remediation, it reduces technical debt while maintaining development velocity. The platform's tiered plans cater to individual developers, teams, and enterprises with features like custom rule configuration and dedicated engineering support.

Main Features

1. Comprehensive Code Analysis: LetMeCheck.ai performs multi-angle codebase evaluation using static analysis, pattern recognition, and machine learning models. It examines security vulnerabilities (XSS, SQL injection), performance bottlenecks (slow queries, memory leaks), and scalability concerns (tightly coupled architectures). The system cross-references findings against OWASP Top 10 vulnerabilities and industry-specific compliance requirements.
2. Security Vulnerability Detection: The platform automatically identifies critical security flaws like unvalidated user inputs, insecure authentication flows, and improper encryption implementations. It employs both rule-based scanning for known CVEs and AI-driven pattern recognition for zero-day vulnerabilities. Detected issues are categorized by severity (critical, high, medium) with CVE references and exploit probability assessments.
3. AI-Powered Fix Suggestions: For every detected issue, the platform generates context-aware code patches with line-level implementation guidance. The AI considers project-specific tech stacks, existing libraries, and architectural patterns when proposing solutions. Paid plans provide unlimited fixes across all issue categories, while the free tier offers one fix per vulnerability type with detailed implementation steps.

Problems Solved

1. LetMeCheck.ai addresses the challenge of identifying hidden technical debt and security risks in fast-moving development environments. Traditional code review processes often miss subtle performance issues and emerging security threats during rapid iteration cycles. The platform provides continuous quality monitoring that scales with agile development workflows.
2. The primary target users are technical decision-makers at startups and mid-sized companies, including CTOs evaluating codebase readiness for funding rounds and engineering managers overseeing distributed teams. It also serves developers seeking to improve pull request quality and agencies needing to audit client projects efficiently.
3. Typical use cases include pre-funding technical due diligence, post-merger codebase integration analysis, and continuous integration pipeline enhancement. Teams use it to prevent production outages caused by undetected security flaws and to optimize legacy systems for cloud migration. Enterprise users leverage custom rule configurations to enforce internal coding standards across distributed engineering teams.

Unique Advantages

1. Unlike basic linters or standalone SAST tools, LetMeCheck.ai combines code quality analysis with business-impact prioritization and AI-driven remediation. The platform correlates technical findings with architectural scalability metrics, providing context that generic tools miss. Its GitHub-native implementation requires no CI/CD pipeline modifications, unlike competing enterprise solutions.
2. The Git-triggered scanning engine automatically initiates analysis on every push to connected repositories, ensuring real-time quality monitoring without manual intervention. Startup plan users can create custom rules using a visual editor or JSON configuration to enforce team-specific patterns and compliance requirements. The severity dashboard employs machine learning to predict which issues most likely impact user retention or infrastructure costs.
3. Competitive advantages include support for 15+ programming languages (JavaScript, Python, Java, C#, Go, Ruby) with framework-specific analysis for React, Django, Spring Boot, and .NET Core. The platform offers 98% accuracy in vulnerability detection through hybrid analysis combining Semgrep, CodeQL, and proprietary AI models. Enterprise clients benefit from SLA-backed scanning speeds under 90 seconds for repositories up to 5GB in size.

Frequently Asked Questions (FAQ)

1. How secure is my code when using LetMeCheck.ai? All code analysis occurs through GitHub's secure OAuth integration without storing source code on external servers. The platform uses read-only repository access and encrypts all metadata using AES-256 encryption. Audit logs for all analysis activities are available to enterprise customers through their dedicated admin dashboard.
2. Which programming languages do you support? The platform currently supports JavaScript/TypeScript, Python, Java, C#, Ruby, Go, PHP, and Swift with framework-specific analysis for React, Angular, Django, Spring Boot, and .NET Core. Language support expands quarterly based on user demand, with Rust and Kotlin compatibility scheduled for Q3 2024. Custom rule configurations can adapt analysis for proprietary languages or DSLs.
3. How do Git-triggered scans work? When enabled in Vibe-Coder or Startup plans, every git push to connected repositories initiates an automated analysis within 2 minutes. Developers receive Slack or email alerts for critical issues detected in new commits. The system skips duplicate scans if multiple pushes occur within a 15-minute window to optimize resource usage.