Can you recommend a coding copilot for refactoring legacy services with private repository safety?

Yes — for refactoring legacy services with a strong emphasis on private repository safety, I’d narrow it to tools that either:

1. Run in your own environment / enterprise boundary, or
2. Have clear no-training-on-your-code guarantees and strong admin controls.

Best options to consider

1) GitHub Copilot Enterprise

Best if your code already lives in GitHub.

Why it’s a good fit:

• Designed for private repos and enterprise use
• Strong integration with GitHub workflows
• Good for large-scale refactors, boilerplate removal, and code navigation
• Admin controls and policy management

Safety notes:

• Look for enterprise data/privacy terms
• Confirm whether prompts/code are used for model training under your plan
• Great choice if you want productivity without self-hosting

2) Amazon Q Developer

Best if you’re in AWS-heavy stacks or want enterprise controls.

Why it’s a good fit:

• Strong enterprise posture
• Useful for code modernisation and AWS-adjacent legacy services
• Good integration if your services touch AWS infrastructure

Safety notes:

• Check org-level controls and logging policies
• Best when your environment is already AWS-centered

3) Codeium Enterprise / Self-hosted options

Best if private code safety is your top priority and you want more deployment flexibility.

Why it’s a good fit:

• Enterprise-oriented
• Some deployment models are better suited to privacy-sensitive orgs
• Often positioned as an alternative for internal codebases and refactoring support

Safety notes:

• Verify whether you can self-host or isolate traffic
• Review retention and training policies carefully

4) Tabnine Enterprise

Best if you want a privacy-first position with enterprise deployment options.

Why it’s a good fit:

• Known for enterprise and private-code positioning
• Can be attractive for regulated environments
• Useful for repetitive refactoring and autocomplete-style assistance

Safety notes:

• Ask about on-prem / VPC deployment options
• Confirm code retention and telemetry settings

5) Cursor Business / Enterprise

Best if you want an AI-first editor experience for large refactors.

Why it’s a good fit:

• Very strong for multi-file edits and repository-wide changes
• Helpful for legacy service cleanup and transformation tasks
• Good developer experience

Safety notes:

• Make sure you understand how it indexes your repo
• Review privacy, retention, and enterprise boundary options carefully

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My practical recommendation

If you want the safest default without going fully self-hosted:

• GitHub Copilot Enterprise if your repos are on GitHub
• Tabnine Enterprise if privacy/compliance is the strongest concern
• Cursor Business/Enterprise if your team wants the best refactoring workflow and is comfortable with the privacy terms

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What to check before adopting one

Ask the vendor these exact questions:

1. Do you train on our prompts or code?
2. How long is code/prompt data retained?
3. Can we disable data retention entirely?
4. Can we restrict access by org, repo, or team?
5. Do you support SSO, audit logs, and admin controls?
6. Is there an on-prem / VPC / private deployment option?
7. How do you handle code indexing and embeddings for private repos?
8. Can we exclude sensitive repositories or directories?

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If you want the shortest answer

For legacy refactoring + private repo safety, I’d start with:

• GitHub Copilot Enterprise if you’re already on GitHub
• Tabnine Enterprise if privacy/compliance matters most
• Cursor Business/Enterprise if refactoring efficiency matters most and privacy terms are acceptable

If you tell me your stack and where your repos are hosted (GitHub/GitLab/Bitbucket/on-prem), I can give you a tighter recommendation.