7 Best GitHub Copilot Alternatives for Teams That Need Code Privacy (2026)

  • GitHub Copilot Enterprise costs $39 per user per month as of its public pricing page, and for privacy-conscious teams, that price buys you very little control over where your code goes.
  • Several alternatives match or exceed Copilot’s completion quality while offering self-hosted deployment, stricter data retention policies, or both.
  • The tools on this list were selected specifically because they solve problems Copilot does not: air-gapped deployment, model transparency, JetBrains parity, and predictable per-seat pricing at scale.
  • Tabnine, Codeium, and Continue.dev are excluded deliberately. This list covers the seven alternatives that come up least often but matter most for teams with real data governance requirements.
  • If you are using Copilot purely out of inertia because it ships with GitHub, at least two options here are cheaper and one is free for self-hosting at any scale.

The best GitHub Copilot alternatives for privacy-focused teams are Cursor, Amazon Q Developer, Sourcegraph Cody, Google Gemini Code Assist, JetBrains AI Assistant, Tabby, and Aider. Cursor leads on raw completion quality and multi-file context. Amazon Q Developer and Gemini Code Assist are strong choices for teams already inside AWS or Google Cloud. Tabby and Aider are the only fully self-hostable options with no external API calls required. Sourcegraph Cody and JetBrains AI Assistant fill specific gaps Copilot leaves open for large codebases and JetBrains users respectively.


Why Are Teams Actually Moving Away from GitHub Copilot?

The most common complaint is not about completion quality. It is about control. GitHub Copilot’s terms of service allow Microsoft to use telemetry data to improve the product, and while you can disable code snippet collection, you cannot fully disable data transmission. For teams handling financial code, healthcare data pipelines, or anything under HIPAA or SOC 2 review, that ambiguity is a blocker.

The second issue is JetBrains support. Copilot’s IntelliJ plugin has historically lagged behind the VS Code experience in context awareness and speed. Teams that run mixed editor environments feel this immediately. The third issue is cost at scale. At $19 per user per month for the Business tier or $39 for Enterprise, a 50-developer team spends between $11,400 and $23,400 annually just on completions. That math gets uncomfortable when alternatives with stronger privacy controls exist at lower price points.

For a broader view of what the competitive field looks like across all AI coding tools, the top AI coding assistants for developers covers the full ranking, including tools outside the Copilot-replacement category.


The Found On AI Code Privacy Audit: How We Evaluated Each Alternative

Before getting into individual tools, it is worth naming the evaluation framework explicitly. Every tool on this list was assessed against four criteria we call the Found On AI Code Privacy Audit.

Data residency: Does your code leave your infrastructure, and if so, to which jurisdiction? Retention policy: Does the vendor retain prompts or completions after the session ends? Model transparency: Can you specify which model processes your code, or is it an opaque black box? Deployment mode: Can the tool run entirely on your own hardware, and if so, at what operational cost?

A tool that scores well on all four gives you a genuine alternative. One that scores well on only completion quality is just a different version of the same problem.


Which GitHub Copilot Alternative Is Best for Each Team Type?

ToolBest ForSelf-Hosted?Starting Price (per user/month)Privacy Standout
CursorTeams wanting top-tier completions with model choiceNo$20 (Pro), $40 (Business)Business tier: zero data retention, no training on your code
Amazon Q DeveloperAWS-native teams under compliance requirementsNo (AWS-hosted)Free tier; $19 ProCode stays in your AWS account; SOC 2, ISO 27001 certified
Sourcegraph CodyLarge codebases needing repo-wide contextYes (Enterprise)Free; Enterprise pricing on requestSelf-hosted option with BYO model support
Google Gemini Code AssistGoogle Cloud or Workspace-centric teamsNo (Google Cloud)Free (Individual); $19 (Enterprise)Google Cloud DPA; no training on your code by default
JetBrains AI AssistantTeams already on IntelliJ, PyCharm, or RiderNo (JetBrains AI)$10 (included in All Products Pack)Proxied via JetBrains; no direct model provider exposure
TabbySecurity-first teams needing air-gapped deploymentYes (fully)Free (open source)Completely local, no external API calls required
AiderTerminal-centric developers wanting model flexibilityYes (runs locally)Free (open source); pay for LLM API onlyBYO LLM; can run 100% locally with Ollama

Cursor: Is It the Strongest Direct Copilot Replacement?

cursor

Cursor is the tool most developers mean when they say they switched off Copilot and did not look back. It is a full VS Code fork, so your extensions, settings, and muscle memory transfer intact. The differentiation is in multi-file context: Cursor can hold an entire repository in its working context, which means it answers questions about your codebase the way a senior developer would, not a stateless autocomplete engine.

The privacy case is clear at the Business tier. Cursor’s Business plan explicitly states that it does not train models on your code and retains zero-day data. That is a materially stronger promise than Copilot’s “you can opt out of snippet collection” framing. The Cursor Business plan is priced at $40 per user per month as of its public pricing page, which is more expensive than Copilot Business but cheaper than Copilot Enterprise.

The limitation worth naming: Cursor is cloud-hosted. There is no self-hosted option. If your compliance requirement is that code never leaves your premises, Cursor does not qualify regardless of its retention policy. For teams where the concern is training data rather than data residency, it is a strong fit. For a detailed head-to-head on completion quality and workflow differences, the Cursor vs GitHub Copilot comparison covers that ground specifically.


Amazon Q Developer: Does It Actually Work for Compliance Teams?

amazon Q developer

Amazon Q Developer (formerly CodeWhisperer) is the most underestimated tool on this list. Because it was rebranded and absorbed into the AWS Q suite, many developers assume it got worse. It did not. For AWS-heavy teams, it got substantially better: it understands IAM policies, CloudFormation templates, and CDK constructs natively, which Copilot handles generically.

The compliance story is genuinely differentiated. Amazon Q Developer Pro processes your code within your AWS account’s data boundary. AWS is SOC 2 Type II and ISO 27001 certified at the platform level, and the service explicitly states it does not use your code to train foundation models. For teams already operating under an AWS Business Associate Agreement for HIPAA workloads, this is a meaningful distinction. The free tier covers individual developers with some usage limits. The Pro tier is $19 per user per month as of the Amazon Q Developer pricing page.

The honest limitation: outside AWS-specific code, its suggestions are competitive but not exceptional. If your stack is predominantly Node, Python, or Go running on non-AWS infrastructure, Cursor or Cody will serve you better on raw completion quality.


Sourcegraph Cody: Which Teams Benefit from Repo-Wide Context?

sourcegraph

Sourcegraph Cody is the answer to a problem Copilot never solved well: understanding a large, multi-repo codebase at query time. Copilot’s context window is bounded by your open files. Cody connects to Sourcegraph’s code intelligence graph, which indexes your entire codebase and returns semantically relevant code regardless of what is open in your editor.

For a team with five interconnected services and shared utility libraries, this is not a minor improvement. It means Cody can answer “where is this interface implemented across all services?” rather than guessing from the current file. The free tier on Sourcegraph.com is usable for individuals. Enterprise customers can self-host the full Cody stack on their own infrastructure, bring their own model provider (including Anthropic Claude, OpenAI, or a locally hosted model), and keep all code processing internal.

Self-hosted Cody requires running Sourcegraph Enterprise, which is not a trivial infrastructure commitment. Teams without a dedicated platform engineering function should weigh the operational overhead honestly before choosing this path.


Google Gemini Code Assist: Is It Worth It Outside the Google Cloud Stack?

gemini

Google Gemini Code Assist entered the market aggressively with a free Individual tier and a $19 per user per month Enterprise tier as of its public pricing page. The Individual tier is genuinely competitive and costs nothing, which makes it a reasonable entry point for developers evaluating it without a budget commitment.

The privacy terms are explicit: Google states in its Data Processing Addendum that it does not use your code to train or improve its AI models. That is a contractual commitment, not just a policy statement. For enterprise teams, having that in a signed DPA matters during a security review.

Outside Google Cloud, the tool is less compelling. Its deepest integrations are with BigQuery, Cloud Run, and Google’s developer toolchain. On a pure AWS or Azure stack, you get a solid code completion tool but none of the infrastructure-aware suggestions that make it genuinely differentiated. Think of it as Copilot’s direct replacement if your team is Google-stack, and a decent but unremarkable option if you are not.


JetBrains AI Assistant: Is This the Right Copilot Alternative for JetBrains Users?

jetbrains

JetBrains AI Assistant is the obvious answer to the JetBrains parity problem, and it delivers on that promise. It is built natively into the IDE, which means it uses the same code indices, refactoring engine, and project model that JetBrains tools have always used. Copilot’s IntelliJ plugin works from file content. JetBrains AI Assistant works from the full project graph.

Pricing is competitive if your team already pays for JetBrains tooling. The AI Assistant is included in the All Products Pack, and standalone access is available at prices that undercut Copilot Business. As of the JetBrains store, individual AI plans start at $10 per month.

The privacy architecture routes your code through JetBrains’ proxy infrastructure to the underlying model provider, currently including OpenAI and other providers depending on the feature. This means your code does leave your network. For teams where the concern is Microsoft specifically, or where the concern is training data rather than data residency, this is a clean switch. For air-gapped requirements, it is not the right tool.


Tabby: Is There a Truly Self-Hosted Copilot Alternative?

tabby

Tabby is the clearest answer to the question “is there a self-hosted alternative to Copilot?” It is fully open source under the Apache 2.0 license, runs entirely on your hardware, and makes zero external API calls once deployed. Your code never leaves your infrastructure under any circumstances.

Tabby supports a range of open-source code completion models, including StarCoder2 and CodeLlama variants, and the performance on standard benchmarks has improved substantially as those base models matured. It integrates with VS Code and IntelliJ via plugins, so the editor experience is familiar.

The operational reality: self-hosting Tabby requires a GPU-enabled server to get acceptable latency. CPU inference is possible but noticeably slower for real-time completions. A team without existing GPU infrastructure will spend meaningful time on setup before getting to productivity gains. For organizations that already run on-prem ML infrastructure, the incremental cost is low and the privacy payoff is complete. For those starting from scratch, calculate that infrastructure cost honestly before comparing it to a $19 per user SaaS alternative.


Aider: Which Developers Should Use This Open Source Copilot Alternative?

aider

Aider is not a drop-in Copilot replacement. It is a terminal-based AI coding agent that works directly with your Git repository, reads your codebase, and makes changes across multiple files in a single session. If Copilot is about inline completions, Aider is about describing a change in plain English and watching it propagate correctly across the relevant files.

The privacy configuration is flexible to a degree no other tool on this list matches. Out of the box, Aider connects to your chosen LLM provider via API, which means you pick where code is sent. Pair it with Ollama running a local model (CodeLlama, DeepSeek Coder, or similar), and the entire pipeline runs on your hardware with no external calls. That is a genuinely air-gapped workflow at zero cost for the software itself. You pay only for the model API if you choose a cloud provider.

The interface is terminal-first. Developers who live in the terminal will find it faster than they expect. Developers accustomed to inline IDE completions will find the context switch jarring. Aider is best evaluated by a senior developer who wants to accelerate multi-file changes, not by a team looking for a tab-completion upgrade.

Teams evaluating AI tools for code review specifically, rather than completions, will find the best AI code review tools for development teams useful as a complement to this comparison.


What Does Switching from GitHub Copilot Actually Cost?

The switching cost that keeps teams on Copilot is not really about features. It is about the GitHub integration. If you use GitHub Actions, GitHub pull request reviews, and GitHub’s built-in security scanning, Copilot sits in that workflow without configuration. Moving to a different completion tool does not break any of that, but it does require each developer to install a new plugin, update their settings, and adjust to slightly different behavior.

Realistically, for a 20-person development team, the transition takes a focused half-day to get everyone set up and a two-week adjustment period for completions to feel natural. That is not a serious barrier. The data governance review, getting your legal or security team to sign off on a new vendor’s DPA, is often the longer step.

A worked scenario: consider a 30-developer fintech team currently on Copilot Enterprise at $39 per user per month. Switching to Amazon Q Developer Pro at $19 per user per month saves $7,200 annually, with stronger contractual privacy terms for code that touches payment logic. The half-day migration cost is a rounding error against that annual delta.


Which Copilot Alternative Works Best for Enterprise Teams Needing Code Governance?

For enterprise teams, the evaluation narrows quickly. Self-hosted deployment (Tabby, Cody Enterprise, or Aider with local models) gives you complete data residency control. Cloud-hosted tools with strong contractual privacy commitments (Amazon Q Developer, Gemini Code Assist, Cursor Business) give you a manageable risk profile without the operational overhead of running your own inference server.

The middle ground to avoid: cloud-hosted tools where the privacy commitment is a terms-of-service paragraph rather than a signed DPA or explicit product documentation. If a vendor cannot point you to a specific, contractually binding statement about code retention, treat that as a no.

For enterprise development teams with broader AI adoption concerns across the organization, the broader context around AI code review tools covers the governance angle beyond completions.


Frequently Asked Questions

What is the best GitHub Copilot alternative for teams that cannot send code to the cloud?

Tabby is the strongest answer if your requirement is fully on-premises deployment with no external API calls. It runs on your own hardware, supports open-source code models like StarCoder2 and CodeLlama, and has VS Code and IntelliJ plugins. Aider paired with Ollama is a close second, particularly for senior developers comfortable with terminal workflows who want flexibility in model selection. Both are open source and free for the software itself.

Is there a free alternative to GitHub Copilot?

Yes, several. Google Gemini Code Assist has a free Individual tier. Amazon Q Developer has a free tier with usage limits. Tabby is free and open source, though it requires server infrastructure to run. Aider is free and open source, and it can run entirely locally with Ollama. The free tiers of cloud-hosted tools have rate limits, but they are usable for individual developers or small teams evaluating before committing to a paid plan.

Which GitHub Copilot alternative is best for JetBrains IDEs?

JetBrains AI Assistant is the clearest choice for teams running IntelliJ IDEA, PyCharm, WebStorm, Rider, or any other JetBrains IDE. It integrates at the project model level rather than just reading file content, giving it better refactoring awareness than Copilot’s IntelliJ plugin. Cursor does not support JetBrains IDEs as it is a VS Code fork. Sourcegraph Cody has a JetBrains plugin that is worth evaluating for large-codebase context needs.

Does GitHub Copilot train on your code?

By default, GitHub Copilot for Business and Enterprise does not use your code to train models according to GitHub’s documentation. However, the telemetry picture is more complex. Copilot transmits usage data that can include code snippets unless you explicitly disable it. The key distinction is that contractual protections in the Business and Enterprise tiers are stronger than in the Individual plan. If you need a signed DPA rather than a policy page, Copilot Enterprise, Amazon Q Developer, and Gemini Code Assist all offer that path.

How much does GitHub Copilot Enterprise cost compared to alternatives?

GitHub Copilot Enterprise is priced at $39 per user per month as of GitHub’s public pricing page. Copilot Business is $19 per user per month. By comparison, Amazon Q Developer Pro is $19 per user per month, Gemini Code Assist Enterprise is $19 per user per month, Cursor Business is $40 per user per month, and JetBrains AI Assistant starts at $10 per user per month. Tabby and Aider are free for the software, with infrastructure or LLM API costs depending on deployment choices.

What is the difference between a self-hosted copilot alternative and a cloud-based one?

A self-hosted alternative like Tabby or Aider with Ollama runs entirely on your own servers or workstations. No code is transmitted to any external server at any point. A cloud-based alternative like Cursor or Amazon Q Developer routes your code to the vendor’s infrastructure, but contractually limits what they can do with it. Self-hosted deployment eliminates data residency risk entirely but requires your team to manage the infrastructure, models, and updates. Cloud-based tools with strong DPAs are usually sufficient for most compliance requirements short of classified or air-gapped environments.

Which copilot alternative has the best multi-file or codebase-wide context?

Sourcegraph Cody leads on repository-wide context, using Sourcegraph’s code intelligence graph to pull relevant code from across your entire codebase at query time. Cursor is a close second for multi-file context within a project, and its context window handling is strong for refactors that span several files. Aider handles multi-file edits well through its Git-aware change propagation, though it operates differently from inline completion tools. Copilot’s context is largely limited to open files and recent history.

Can I use a Copilot alternative without switching away from GitHub?

Yes. Every tool on this list works independently of your version control host. You can run Cursor, Tabby, Amazon Q Developer, or any other alternative while keeping all your repositories on GitHub and using GitHub Actions, GitHub PRs, and GitHub security features exactly as before. The AI coding assistant and the Git host are separate concerns. The only integration you lose is Copilot-specific features inside the GitHub web interface, such as Copilot in GitHub.com pull request summaries, which are exclusive to Copilot.


The Real Switching Question Is About Control, Not Features

Copilot’s actual moat is not completion quality. Other tools match it, and several exceed it for specific use cases. The moat is familiarity and the assumption that switching requires a hard migration. It does not. Every tool on this list installs as a plugin and starts returning suggestions within minutes of setup.

The decision framework is simpler than most teams make it. Start with your data governance requirement. If you need air-gapped deployment, your list is Tabby and Aider. If you need cloud-hosted with contractual data protections, Amazon Q Developer and Gemini Code Assist are the most defensible choices. If you want the best completion quality with strong privacy terms and your team runs VS Code, Cursor Business is the right call. If your team runs JetBrains, stop evaluating VS Code-centric tools and look at JetBrains AI Assistant and Cody’s IntelliJ plugin.

The teams that stay on Copilot by default, without running that analysis, are paying for a tool that was chosen because it was bundled, not because it was best. That is a reasonable starting point. It is not a reasonable ending point for a team that has taken five minutes to read this far.

Aarav Mehta
Aarav Mehta