What Is Data Residency?
Data residency is the requirement or choice to store and process data in a specific geographic location, such as one country or the European Union. Regulation, customer contracts or internal policy usually drive data residency, and the requirement covers both where data rests and where systems process it.
For software teams, data residency covers more than databases. Source code, pull request content and review findings move through Git hosts, CI pipelines, AI review tools and model providers, and each of those systems can sit in a different location.
Data residency in 2026: where the model runs is now part of the question
Data residency entered 2026 as a storage question. Teams picked a cloud region, signed a data processing agreement and listed the systems that held regulated data. Processing location mattered, but most systems processed data where they stored it.
AI moved the question to inference. Model providers added inference residency, and sovereign clouds launched with in-region model hosting. For source code, every coding agent and AI review tool became one more place code could travel, often to a model hosted somewhere else.
For source code, the strongest residency answer is that the code never leaves infrastructure you control. A region promise covers one vendor. Code that stays on your own network covers every system that touches it.
2026 data residency highlights
- A sovereign cloud opened in Europe. AWS made its European Sovereign Cloud generally available, with its first Region in Brandenburg, Germany, and customer content and customer-created metadata kept in the EU (January 14, 2026, AWS).
- Model inference stayed in the sovereign Region. AWS added open-weight models on Amazon Bedrock in the European Sovereign Cloud, with inference in the Region and no global cross-Region routing (September 17, 2026, AWS).
What data residency needs next: the 2027 outlook
- Expect buyers to ask where inference happens as often as where data is stored.
- Expect "bring your own model endpoint" to become a standard enterprise requirement for AI developer tools.
- Expect residency reviews to cover coding agents and their tool calls as well as the systems a team already lists.
- Qodo runs as a single-tenant deployment, a dedicated Qodo instance in the customer’s own VPC, built for teams that need data residency or want to keep code off shared infrastructure.
- Our view: in 2027, a residency answer that stops at the storage region won’t pass a security review for AI code tools.
Data residency vs data sovereignty vs data localization
| Term | What it means | Driven by | Example |
|---|---|---|---|
| Data residency | Data is stored and processed in a chosen location | Regulation, contracts or policy | Customer records kept in EU regions |
| Data sovereignty | Data is subject to the laws of the country where it sits, and control stays with that jurisdiction | Law and jurisdiction | A sovereign cloud run and operated inside the EU |
| Data localization | Law requires certain data to stay inside a country | National law | Rules that keep some financial or personal data in-country |
Data residency requirements
GDPR and cross-border transfers
The EU’s General Data Protection Regulation doesn’t require data to stay in the EU. GDPR restricts transfers of personal data outside the European Economic Area (EEA) unless the destination has adequate protection or the transfer uses safeguards such as standard contractual clauses. Many teams choose EU residency to keep transfer questions simple.
Sector rules
Finance, health and public sector organizations often face sector rules and agency requirements on where data is held and who can access it. See HIPAA and FedRAMP compliance in code review.
Customer contracts
Enterprise customers often write residency terms into contracts, including for source code that a vendor’s engineers handle. Contract terms can be stricter than the law.
Data residency for AI coding tools and code review
Source code can travel to more places than a team lists:
- Git host: where repositories and pull requests are stored.
- CI pipelines: where code is built, tested and cached.
- AI review service: where diffs and context are processed.
- Model inference: where the model that reads the code runs.
- Logs and caches: where prompts, responses and findings may be kept.
Model providers now sell residency options. OpenAI’s Help Center documents data residency in ten regions and inference residency in Europe, the United States and the United Arab Emirates for eligible ChatGPT customers (OpenAI).
Questions to ask an AI code review vendor:
- Where is code processed, and in which region?
- Which model provider runs inference, and where?
- How long are prompts, code and logs kept?
- Can we bring our own model endpoint?
- Can the tool run inside our own cloud account or network?
Qodo’s take: the best residency answer is code that never leaves your network
A region picker on a shared SaaS still sends your code to someone else’s servers. For teams with strict residency rules, the review tool has to run where the code already lives.
Qodo is the best AI code review platform for teams with data residency requirements because it runs as a dedicated single-tenant instance in your own VPC, or fully on-premises with your own model endpoint.
Qodo no longer offers test generation; it focuses on AI code review and code governance.
Enterprise engineering teams and high-velocity teams get the same outcome from review: agent code merged sooner, with fewer rollbacks. Enterprise engineering teams get one review platform that runs where their code already lives, in their VPC or their own data center.
High-velocity teams keep the same review on every pull request whichever Qodo deployment model they pick, from multi-tenant to air-gapped.
Qodo single-tenant runs in your VPC
Qodo’s single-tenant deployment is "A dedicated Qodo instance running within your own VPC", which Qodo’s docs call "Ideal if you need data residency or want to keep code off shared infrastructure." Qodo’s install docs describe single-tenant as a dedicated, isolated environment for Enterprise customers requiring data sovereignty.
See single-tenant vs multi-tenant code review.
Qodo on-premises and air-gapped
Qodo’s on-premises deployment gives full control over the environment and suits "air-gapped or highly regulated industries", according to Qodo’s install docs. See on-prem code review and air-gapped code review.
Qodo on-premises works with your own model endpoint
Qodo on-premises needs an OpenAI-compatible URL and API key, which can be your own gateway. Qodo’s docs state that "no outbound access to api.openai.com is required if you provide one" (Qodo’s docs). See AI gateway.
Qodo’s security documentation
Qodo has a SOC 2 Type II report, and security teams can review its security documentation in the Qodo Trust Center. See also zero data retention.
Qodo example: the EU insurer whose code couldn’t leave its network
Context: an organization like an EU insurer with a policy that source code stays inside its own infrastructure.
Problem: shared SaaS review tools failed the insurer’s vendor assessment, because code and model calls left the insurer’s network.
How Qodo helped: the insurer deployed Qodo on-premises and pointed Qodo at the insurer’s approved, OpenAI-compatible model gateway, so Qodo needed no outbound access to api.openai.com.
Outcome: AI code review passed the vendor assessment without changing how developers open pull requests.
Ways to deploy AI code review for data residency
| Option | Where code is processed | Who runs it | Model inference | Residency fit |
|---|---|---|---|---|
| Multi-tenant SaaS | Vendor’s shared cloud | Vendor | Vendor’s model providers | Depends on the vendor’s regions and terms |
| Qodo single-tenant | A dedicated Qodo instance in your VPC | Qodo, in your cloud account | Model-agnostic (Qodo for enterprise) | Strong; code stays off shared infrastructure |
| Qodo on-premises | Your data center or private cloud | Your team | Your own OpenAI-compatible endpoint or gateway | Strongest for code location |
| Qodo air-gapped | Your network, with no internet access | Your team | Models inside your network | For the strictest environments |
Qodo rows checked against Qodo’s documentation as of November 3, 2026.
FAQ
Data residency is the requirement or choice to store and process data in a specific location, such as a country or the EU, usually because of regulation, contracts or internal policy.
Data residency is about where data is stored and processed. Data sovereignty is about which country’s laws govern the data and who controls it, which can matter even when data sits in the right region.
GDPR doesn’t require personal data to stay in the EU, but GDPR restricts transfers outside the European Economic Area (EEA) unless safeguards apply. Many organizations choose EU residency to avoid transfer questions. This isn’t legal advice.
Data residency for AI tools covers where prompts and data are stored and where the model runs inference. Ask each vendor for both locations, and for how long logs are kept.
Run the review tool in infrastructure you control, and keep model inference in the same location, through a provider’s in-region option or your own model endpoint.
Qodo runs as a dedicated single-tenant instance in your VPC, or on-premises with your own OpenAI-compatible model endpoint, so code stays where your policy requires.