Mend AI
A security tool that inventories every AI model, prompt, and dataset a company uses and flags risky or unapproved ones.
A one-click AI fix feature inside a code-scanning tool, proposing corrections for quality and security issues right in the editor.
AI CodeFix is an AI feature inside SonarQube, a code quality and security scanning tool that flags bugs, vulnerabilities, and maintainability issues in source code. When a developer asks, it generates a proposed fix for a flagged issue and shows it directly in their editor through the SonarQube for IDE extension, which covers VS Code, IntelliJ, Cursor, and Windsurf. The developer reviews each fix and can apply, edit, or discard it before it reaches the codebase. It supports Java, JavaScript, TypeScript, Python, C#, C, and C++. SonarQube is made by Sonar. In SonarQube Cloud it uses OpenAI's GPT-4o or Anthropic's Claude; in the self-managed Server version it uses a customer's own Azure OpenAI deployment.
This fits a team already running SonarQube for code quality gates that wants to close the gap between finding an issue and fixing it. It comes at no extra cost on SonarQube Cloud's Team and Enterprise plans and the self-managed Server's Enterprise and Data Center editions, so an existing customer on those tiers can turn it on without a new contract; lower-tier plans do not include it. The Cloud Team plan starts near $32 a month as a planning figure, and Sonar prices self-managed editions by lines of code analyzed, so confirm current pricing directly. Because a developer must approve every suggested fix, it will not save time on its own; a review habit needs to already be in place.
The industries and leadership roles this tool is most often matched with.
How one company factor at a time moves the modeled score. The published score is unchanged.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $54.4K | $85.5K | $137.2K |
| Three-year total | $118.1K | $177.9K | $274.3K |
| First-year cost per unit | $54.4K | $85.5K | $137.2K |
| Average annual cost per unit (over three years) | $39.4K | $59.3K | $91.4K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $18K | $24K | $32.4K |
| Implementation | $8.4K | $14K | $23.8K |
| Integration | $9.9K | $18K | $32.4K |
| Staff time and change management | $6K | $8.5K | $11.9K |
| Security | $4.6K | $6.5K | $9.8K |
| Administration | $3.4K | $4.5K | $6.1K |
| Support | $1.7K | $2.2K | $3K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 1 production deployment. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of SonarQube AI CodeFix and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Export MCP server definitions, tool schemas, and repository scopes, plus custom rules, prompts, codebase indexes, agent plans, chat history, evaluation results, usage analytics, provider settings, and tool configuration from SonarQube AI Code Assurance. Keep authoritative source records in Azure. Accepted code should remain in Git or the system of record, but indexes and agent workflows may not; revoke repository and model tokens and require deletion of indexed proprietary code.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
A security tool that inventories every AI model, prompt, and dataset a company uses and flags risky or unapproved ones.
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Research observations recorded: 1. Evidence quality: Some support.
Recorded score and category rank across research updates.
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