Typo - Measure AI's Impact on Code Quality

Measure AI's real impact on code, quality, and delivery

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Updated Jul 2026 · Added Jul 2026

typoapp.io

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What is Typo?

Typo is an engineering intelligence platform that measures AI's real impact on code quality, delivery speed, and developer experience across your software development lifecycle. It connects engineering signals from your SDLC into one intelligent layer, providing visibility into AI adoption, code review insights, and productivity metrics. Built for engineering leaders and teams who need to understand how AI is transforming their development processes and make data-driven decisions about AI tools and practices.

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Key Features of Typo

AI impact measurement across delivery speed, code quality, and developer experience
Track AI adoption and code written using AI across teams
Context-aware AI code reviews trained on your codebase
DORA metrics and productivity tracking out of the box
AI-powered engineering sidekick for instant answers
MCP server integration with Claude Code and Cursor
Developer experience measurement with research-backed signals
Work allocation and PR cycle time tracking
Security risk detection during development
Goal setting, benchmarking, and alert creation

Who Should Use Typo?

Measure real ROI of AI tools on delivery speed and code quality

Identify AI champions and best practices within engineering teams

Catch security risks and bugs before production deployment

Optimize PR review cycles and reduce review time

Track developer productivity and work allocation in real time

Align teams around engineering metrics and delivery health

Improve developer experience by identifying bottlenecks

Typo: Pros & Cons

✓Pros

Real engineering data for measuring AI impact instead of guessing
Fully codebase-aware AI reviews that understand system connections
Out-of-the-box DORA metrics and productivity tracking
Continuously learning AI that improves with feedback
Integration with popular AI agents via MCP server
Instant visibility across entire SDLC
Identifies top AI performers and learning opportunities

Frequently Asked Questions about Typo

What does Typo measure about AI impact?

Typo measures how AI is impacting delivery speed, code quality, and developer experience using real engineering data from your SDLC. It tracks AI adoption, cycle time, review time, and overall delivery speed to help you understand real ROI.

How does Typo's AI code review work?

Typo provides context-aware, signal-first AI reviews that are trained on your codebase, rules, and engineering patterns. It builds a living graph of your codebase to understand how systems connect, catching real impact and security risks before they reach production.

Can Typo integrate with AI agents?

Yes, Typo has an MCP server that brings your PR history, code health, and delivery signals directly into Claude Code, Cursor, and any MCP-compatible agent.

What metrics does Typo track out of the box?

Typo tracks developer productivity metrics including work allocation, PR cycle time, DORA metrics, sprint predictability, and more across your entire SDLC.

How does Typo help identify top performers?

Typo identifies who is using AI most effectively across your teams and provides insights into what others can learn from your AI champions.