Radically different codebase intelligence

Where AI-generated code meets production-grade quality to review, secure, monitor or metricise every pull request.

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Code + Quality = Codity

What happens between opening a pull request and merging it.

  1. Connect

    Point Codity at a repository on GitHub, GitLab, Bitbucket or Azure DevOps. The webhook registers itself.

    POST /webhooks/codity → 201

  2. Index

    It reads the whole repository rather than the diff: every service, every dependency, and the tickets the work came from.

    indexed 1,284 files · 37 services

  3. Review

    Every pull request comes back with findings ranked by what actually breaks, each one on the line that causes it.

    review #482 · 3 blocking · 6 suggestions

  4. Ship

    Take the patch straight from the comment or push your own. The dashboard keeps the trend across repositories.

    suggestion applied · commit pushed

See it run on your codebase

With AI, code quality has been a headache. With Codity, it’s a head-start.

  • Every pull request is reviewed using complete codebase context, not just the files that changed. Codity understands your repositories, linked tickets, and service dependencies to catch functional issues, prioritize findings, and provide actionable feedback directly on the pull request.

  • Catch security issues before they reach production. Scan every pull request for leaked secrets, vulnerable dependencies, injection risks, and insecure patterns, with findings surfaced directly where developers work.

  • Understand any codebase in seconds. Search across repositories, trace dependencies, follow execution flows, and instantly discover how services, APIs, and components connect.

  • Measure engineering performance with meaningful insights. Track review efficiency, merge velocity, deployment trends, DORA metrics, and identify bottlenecks across your engineering organization.

  • Stay ahead of production issues with continuous repository intelligence. Detect unusual code changes, quality regressions, and engineering trends before they become incidents.

langchain/langchain⌘K
langchain/schema.py
Comment on lines +225 to +226
225+class ValidationError(BaseModel):
226+    error_message: str
codity.aiBot10 hours ago
Functional

ValidationError is defined with field error_message, but every construction site in this PR passes text=..., so any parse failure crashes before fix() can run.

Suggested fix
Prompt for AI assistance
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No more compromising on speed for quality

A unified platform that keeps quality ahead of every commit.

CLI

Run Codity from your terminal. Review pull requests, scan for security issues, search your codebase, and integrate seamlessly into local workflows or CI/CD pipelines.

Memory

Learns how your team reviews code. Codity remembers review decisions, accepted suggestions, and engineering preferences to deliver more consistent reviews with fewer repeated comments.

Custom Rules & Policies

Automate your engineering standards. Define repository or folder-specific rules, enforce coding policies, require tests, validate architectural decisions, and apply custom review workflows across every pull request.

Integrations

Connect with your existing developer stack. Integrate GitHub, GitLab, Azure DevOps, Bitbucket, Jira, Linear, Slack, Microsoft Teams, webhooks, and more to bring complete context into every review.

Security Notifications

Know the moment a risk appears. Receive real-time alerts for leaked secrets, vulnerable dependencies, and critical security findings through Slack, Microsoft Teams, email, or webhooks.

Production Incident Response

Resolve incidents faster with AI-powered root cause analysis. Correlate code changes, deployments, logs, metrics, and traces to identify the root cause, generate detailed RCA reports, recommend fixes, and automatically create remediation pull requests when it's safe.

Security first design built for enterprises

  • SOC 2 Type II
  • VAPT
  • HIPAA
  • GDPR

Frequently asked questions