AI code health, purpose-built

What % of your code is AI-generated?
And how is it aging?

Lintara tags AI vs human code at the commit level, scores codebase health continuously, and prioritizes remediation before AI debt compounds.

You're on the list

We'll email you when early access opens. You're going to love what we're building.

41%

New code is AI-generated

Rise in code duplication

Maintenance cost by year 2

The Problem

AI writes fast.
It doesn't write sustainably.

AI coding tools generate functional code at speed. But research shows that code systematically lacks architectural judgment, creates 1.7x more issues in pull requests, and compounds into debt that traditional tools weren't built to detect.

src/services/auth.ts

                    
                    // Token validation with retry logic
                    human
                
                    async function validateToken(token: string) {
                    human
                
                      try {
                    copilot
                
                        const decoded = jwt.verify(token, SECRET)
                    copilot
                
                        return decoded
                    copilot
                
                      } catch(e) { return null }
                    copilot
                
                      // Missing: retry, logging, error types ▲
                
                    }

How Lintara Works

Built for the AI coding era

Everything existing code quality tools should do, but don't.

AI Provenance Tagging

Tag every line as AI or human at the commit level. Track which AI tool generated it. Know exactly what came from Copilot, Cursor, Claude, or your team.

Continuous Health Scoring

Real-time CodeHealth scores split by AI vs human code. See which parts of your codebase are degrading and whether AI code ages differently.

Smart Remediation

Prioritized fix suggestions for AI-specific debt patterns: duplicated blocks, shallow error handling, missing retry logic, architectural anti-patterns.

CI/CD Quality Gates

Block PRs that introduce AI debt above your threshold. Enforce health standards in every pipeline run. Works with GitHub, GitLab, Bitbucket.

Team Analytics

Dashboard showing AI adoption rates per team, debt accumulation trends, and churn metrics. Give engineering leaders the data to make policy decisions.

Compliance Ready

Audit trail for AI code provenance. Know exactly which AI generated what, when, and who approved it. Essential for regulated industries.

Not another SonarQube

Capability	SonarQube	CodeScene	Lintara
AI vs Human tagging	Copilot only	No	All AI tools
AI-specific debt scoring	Generic	Generic	Purpose-built
Commit-level provenance	No	No	Yes
AI debt remediation	Generic fixes	Generic refactoring	AI-pattern specific
Built for AI era	Retrofitted	Retrofitted	Native

AI code is inevitable.
Sustainable AI code isn't.

Every team using Copilot, Cursor, or Claude is accumulating debt they can't see yet. Lintara makes it visible, measurable, and fixable.