GeezerVison is showing codescene.com — Scale AI Coding Safely and Mitigate Technical Debt | CodeScene

Accelerate with AI, without losing control

Scale AI safely, keep code quality high and increase delivery speed. All powered by CodeHealth™, the scientifically validated metric predicting defects and delivery performance.

Leader on G2

Patented solution

AWS partner

ISO 27001 certified

For individual devs For teams

iCodeHealth™

Optimal AI code

Critical: High AI risk

Assess AI Risk

The average enterprise codebase scores 5.15 out of 10 on Code Health. AI needs 9.5 to work reliably. Know exactly where you stand.

Uplift unhealthy code first

AI agents introduce at least 60% more defects and burn up to 50% more tokens in unhealthy code. Reduce tech debt at scale, so agents actually deliver.

Enforce guardrails

Enforce automated guardrails across your team's agentic workflows, preventing technical debt in every AI-generated change.

Empowering the world's top engineering teams

The journey of AI software development

From first pilot to autonomous fleets, without losing the codebase

We help engineering organizations transform safely across three phases, holding Code Health to the 9.5 rule at every step of the journey.

9.5The 9.5 ruleThe bar every merge clears, end to end.

The 9.5 rule

Govern & steer

Purpose

Developer tools

Leadership tools

Risk

Customer proof

Phase 1

Pre-AI

No AI in production dev work or AI only in walled-off test teams.

The 9.5 rule

Code Health 8.1/ 9.5

Set your Code Health baseline and gate every merge before AI lands.

Govern & steer Assess AI readiness, set guardrails

Purpose

Define your productivity baseline
Prioritize technical-debt remediation
Gate your code at the 9.5 bar

Developer tools

Leadership tools

Quality Track Code Health trends across every repository and team. Goals Set and monitor improvement targets per team and per quarter. Organisation See knowledge distribution and bus-factor risk across the org. AI Readiness Gauge whether a codebase is healthy enough to adopt AI safely. PR Engagement Monitor review depth, latency and participation. IDE Engagement See where and how AI assistance is used in the editor.

Risk

Risk without us Code health decline and being unable to adopt AI safely.

Customer proof

-32%critical hotspots

"We mapped our baseline and cleared a third of our worst hotspots before rolling out AI."

Nordic fintech, 220 engineers

Phase 2

AI-Assisted

AI coding assistants in daily use, from team rollout to org-wide governance.

The 9.5 rule

Code Health 9.2/ 9.5

Hold every AI-assisted PR to the 9.5 rule, no drift, no exceptions.

Govern & steer Org-wide policies, gates & PR standards

Purpose

Safeguard AI-generated code
AI-assisted uplift of your code
Measure productivity performance

Developer tools

CH PR Gates Code Health PR Gates. Block merges that drop Code Health below your 9.5 bar. CC PR Gates Code Coverage PR Gates. Enforce test-coverage thresholds on every pull request. IDE Plugin Live Code Health feedback inside the editor, as you type. REST API Pull Code Health and engineering metrics into your own systems. MCP Server Serve CodeScene context to AI agents over the Model Context Protocol. PR Ref. Agent PR Refactoring Agent. Proposes fixes targeted at your real hotspots. CLI Run Code Health checks in any pipeline or agent workflow.

Leadership tools

Quality Track Code Health trends across every repository and team. Productivity Measure delivery throughput and where engineering time is really spent. Goals Set and monitor improvement targets per team and per quarter. Organisation See knowledge distribution and bus-factor risk across the org. PR Engagement Monitor review depth, latency and participation. IDE Engagement See where and how AI assistance is used in the editor. MCP Engagement Track agent activity and context usage across fleets.

Risk

Risk without us Up to 60% higher defect risk. Productivity gains hard to prove.

Customer proof

-38%time in code review

"Every AI-assisted PR now clears the 9.5 bar and review time fell by more than a third."

Global SaaS platform, 600 engineers

Phase 3

Agentic & Autonomous

AI agents take action across supervised, scoped tasks through autonomous fleets.

The 9.5 rule

Code Health 9.6/ 9.5

Bind autonomous agents to the 9.5 rule before any merge reaches main.

Govern & steer Steer agent fleets, trust calibration

Purpose

Safeguard & guide agents
Deploy and scale agentic workflows
Optimize AI performance & token spend

Developer tools

REST API Pull Code Health and engineering metrics into your own systems. MCP Server Serve CodeScene context to AI agents over the Model Context Protocol. CLI Run Code Health checks in any pipeline or agent workflow.

Leadership tools

Risk

Risk without us Degrading agent performance. Token spend climbs 25% to 50%.

Customer proof

-41%token spend

"We scaled supervised agent fleets and cut token spend while throughput kept climbing."

Enterprise infra team, 1,200 engineers

Map your AI readiness Read the research Hover any tool for details. Click to open it.

For Developers

The CodeHealth™ MCP Server creates a self-correcting loop inside your AI coding assistant to safeguard AI-generated code and make legacy code AI-ready.

For Teams

The AI Framework assesses where AI is safe to apply, safeguards AI-ready areas, uplifts unhealthy code for AI at scale, and tracks measurable impact and ROI.

Manage technical debt where it impacts delivery

As AI accelerates development, technical debt scales with it. CodeScene identifies high-impact debt, prevents debt and tracks trends so you can act before delivery slows or quality suffers.

STEP 1

Prioritize and quantify technical debt

CodeScene identifies and prioritizes high-impact technical debt to accelerate delivery and reduce defects. The CodeHealth™ metric makes progress visible as a shared KPI.

STEP 2

Enforce standards with CodeHealth™ reviews

Enforce change with automated CodeHealth™ Reviews. They act as both quality gate and coach, preventing new technical debt without slowing teams down.

STEP 3

Prevent technical debt at the source

Shift left with real-time CodeHealth™ feedback in the IDE. Identify risks early and prevent technical debt from entering your codebase.

Safe AI Coding at Scale

A practical framework to identify where AI works, where it fails, and how to apply it safely across your codebase.

Partners for 6+ years

Maarten Metz

Principal Software Engineer, Philips

“CodeScene has helped us find ways to improve the productivity of our development teams and measure our success. Ultimately improving how quickly we can deliver value to the business.“

Partners for 3+ years

Stuart Caborn

Distinguished Engineer

“We can now explain the business impact of AI-assisted development, backed by data.“

From 0 to 50% agent-assisted code within five months while increasing throughput and maintaining high code quality.

Partners for 2+ years

Lauren Swanson

Lead Software Engineer, Carterra

“At Carterra we reduced unplanned work by 82% over a twelve-month period thanks to CodeScene.”

Partners for 6+ years

Raja Rajeshwar

Principal Software Architect, Philips

"CodeScene is a unique tool that enables management of Technical Debt before it becomes an issue."

Partners for 3+ years

George Malamidis

VP of Engineering, loveholidays

AI’s promise is delivery efficiency, but efficiency without maintainability isn’t progress. CodeScene ensures we know the difference.”

Johannes Buvnäs

CTO, StickerApp

“CodeScene's Code Health Metric is fact-based and is our metric for technical debt. It guides our prioritization and empowers our business with clear metrics to guide our efforts.”

Adam Chapman

Developer, Apex Networks

"We're working with a project that's been around for a solid 15 years. Back in its early days, tight deadlines led to a few shortcuts in the code. Thanks to CodeScene, we can now sift through that technical debt, pinpointing exactly where to channel our efforts for the most impactful improvements."

Jake Maizel

Vice President, Infrastructure and Core Engineering, SoundCloud

"CodeScene provides insights into our development life cycle that no other tool we use can provide."

Johan Nordberg

Software Engineer, Active Solutions

“I’ve added instructions to my Github Copilot to always check with CodeScene MCP server before accepting changes. If the Code Health isn’t good enough, it has to try again. That has made an enormous difference. It’s not just a safeguard, it constantly reminds me to stay disciplined and not blindly accept AI-generated code.”

Xavier Greffe

Scrum Master, Bringme

"CodeScene makes it very easy to surface technical debt and assists in continuously monitoring your Code Health. It even gives you clear instructions on fixing Code Health declines."