Background
GenAI

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 developers For teams
iCodeHealth™
10
9
Optimal AI code
8
7
6
5
4
3
2
1
Critical: High AI risk

Assesstment

Risk assessment and strategic view CodeHealth™ analysis shows in minutes where AI-coding can be safely applied today. Measure and track impact. Enable high ROI.

Safeguard

AI safeguards for AI-ready areas ensure AI-generated code stays aligned with quality and remains AI-ready with CodeHealth™ MCP Server.

Uplift

AI-powered uplift for not-yet-ready areas works best on healthy code. Use CodeScene ACE + MCP to improve problematic code so AI can be applied safely.

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.

9.5 The 9.5 ruleThe bar every merge clears, end to end.
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
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.
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 usCode 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
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. 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. CLI Run Code Health checks in any pipeline or agent workflow. REST API Pull Code Health and engineering metrics into your own systems.
Leadership tools
Quality Track Code Health trends across every repository and team. Productivity Measure delivery throughput and where engineering time is really spent. 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. Goals Set and monitor improvement targets per team and per quarter. Organisation See knowledge distribution and bus-factor risk across the org.
Risk

Risk without usUp 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
MCP Server Serve CodeScene context to AI agents over the Model Context Protocol. CLI Run Code Health checks in any pipeline or agent workflow. REST API Pull Code Health and engineering metrics into your own systems.
Leadership tools
Quality Track Code Health trends across every repository and team. MCP Engagement Track agent activity and context usage across fleets. Goals Set and monitor improvement targets per team and per quarter. Organisation See knowledge distribution and bus-factor risk across the org.
Risk

Risk without usDegrading agent performance; 25% to 50% token-spend increase.

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 Customer results are representative. Tools shown are clickable.

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.

Read more

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.

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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.
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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.

Get CodeScene
AI Playbook

Get the AI Playbook and build a self-correcting workflow.

CodeScene AI Playbook