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Typo

Engineering intelligence platform measuring AI's real impact on delivery speed, code quality and developer experience across the SDLC

paid14-day free trial with no credit card required, and monthly or annual billing with annual advertised at 20% off. Pricing is per developer with a slider covering 1 to 1,000 developers. The Starter plan is $20 per developer per month billed annually, including delivery insights and AI code impact measurement. Higher tiers and enterprise arrangements are quoted via demo.View full pricing →

About Typo

Typo is an engineering intelligence platform that connects a team's SDLC signals — commits, pull requests, reviews, deployments — into one layer and reports what is actually happening to delivery. Its current positioning is squarely on the AI adoption question: leaders can see that developers are shipping more code with AI assistance but cannot tell whether delivery, quality or team health improved. Typo's AI Impact module tracks how much code across teams and individual developers is AI-written, measures the effect of that code on cycle time, review time and overall delivery speed to produce an ROI figure, and identifies which developers are using AI most effectively so their practice can be transferred to others. Around that sit three further modules. Engineering Productivity gives real-time SDLC visibility, work allocation analysis and delivery health metrics out of the box. AI Code Reviews performs context-aware review with automatic fixes. Developer Experience measures a Developer Experience Index, covering the human side that pure throughput metrics miss. Ask AI is a natural-language interface answering questions about code, pull requests, deployments or team performance without building a report. The company publishes engineering benchmarks, an AI Impact guide and a governance framework for measuring and scaling AI impact across the SDLC, and maintains a Trust Center. It is a G2 Spring 2026 category leader and publishes named customer stories including Stackgen, Groundworks and Transfeera.

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Key Features

Measures AI-written code volume and its effect on cycle and review time
Identifies which developers use AI most effectively
Context-aware AI code reviews with automatic fixes
Developer Experience Index alongside throughput metrics
Ask AI answers natural-language questions about PRs, deploys and team performance

Tags

engineering-metricsdoracode-reviewdevexsdlc
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