About
A quality layer for AI-era codebases.
AI tools are writing more code than any team can review by hand. We built Implera to give engineering teams a way to measure what that actually does to a codebase, across the signals that matter.
Why Implera exists
In the last two years the volume of code landing in production has risen sharply. Copilot, Cursor and Claude write a large share of it. The traditional quality net, manual code review, was designed for human-pace development. It cannot keep up.
Teams that move fast need a quality layer that moves at the same speed. Something automated, honest, and explainable. Not another dashboard no one opens. Not a magic AI grade. A clear score you can trust, grounded in real signals from your codebase.
How we build
Deterministic scoring
The score is always produced by structural signals and static analysis. Same code in, same number out. Nothing is left to interpretation at the score level.
AI-assisted, not AI-scored
AI specialist reviews produce findings, summaries and explanations. They add context around the score. They never set it.
Read-only by design
The GitHub App has read permissions only. We never open pull requests, push commits or alter your code. We analyse and report.
Explainable, not opaque
Every score comes with a breakdown of which signals contributed. You can see what moved the number and why.
The team
Implera is a small, focused team. Everyone writes code, talks to users and thinks about quality.
Gareth Clubb
Founder
Founder of Implera. Writes about codebase quality, AI-assisted development and the signals engineering teams should track to ship reliable software.
David White
Product and Engineering
Works on product and engineering at Implera. Writes about code quality, testing practices and keeping dependencies healthy in fast-moving codebases.
Get in touch
Questions about pricing, enterprise use or partnerships? Get in touch. Curious how a codebase scores? Run your first analysis. Our public GitHub org is github.com/Implera-ai.