UK GDPR still applies, even post-Brexit
UK GDPR (sitting alongside the Data Protection Act 2018) applies to any UK-based business processing personal data, and to non-UK businesses offering services to UK residents. If you also have EU customers, EU GDPR applies in parallel and usually needs an EU representative. Most SaaS teams treat the two as one compliance standard because the practical requirements barely diverge.
The obligations bite as soon as you store an email address, IP address, or usage log tied to an identifiable person. There is no size exemption. A five-person SaaS startup has the same core obligations as a 500-person company, just a smaller budget to meet them.
The core obligations that actually shape your schema
Lawful basis has to be decided per data flow, not once for the whole product. Account data usually relies on contract necessity, marketing emails need consent, and analytics often relies on legitimate interest with an opt-out. Each basis has different rules for withdrawal and retention, so the database needs to track which basis applies to which record.
Data minimisation means the product should only collect fields it actually uses. Retention means every table with personal data needs an answer to "how long do we keep this and what deletes it." Subject access and erasure requests need a real code path: export a user's data on request, and delete or anonymise it within statutory timeframes, including from backups and analytics pipelines, not just the primary table.
Data residency, sub-processors, and vendor risk
Every SaaS product runs on a stack of vendors: hosting, email delivery, payments, analytics, error tracking, and increasingly, AI APIs. Each one that touches personal data is a sub-processor and needs a Data Processing Agreement, a documented legal transfer mechanism if it is US-based, and a place on the sub-processor list you show to customers and auditors.
AI vendors deserve specific attention. Sending customer data to an LLM API is a data transfer like any other, but teams often skip the DPA review because the integration feels like "just an API call." Check retention settings, whether the vendor trains on your data by default, and whether you can turn that off contractually, not just via a UI toggle.
Building compliance in instead of bolting it on
The cheapest time to design for compliance is before the first customer signs. That means audit logs on access to personal data, encryption in transit and at rest, role-based access so support staff see only what they need, and a documented incident response plan with the 72-hour regulatory notification window built into the runbook, not discovered during an actual breach.
A practical baseline for most SaaS products: a privacy policy that matches what the code actually does, a sub-processor list kept current, a DSAR workflow that produces a real export and a real deletion, retention rules enforced by a scheduled job rather than a manual process, and a named person (not necessarily a full DPO) responsible for keeping all of it up to date as the product changes.
International transfers: SCCs and the UK IDTA
Most SaaS stacks send data outside the UK the moment they touch a US-headquartered cloud provider, email service, or AI API — even if the servers are in an EU or UK region, the parent company's legal jurisdiction can still matter for transfer purposes. For transfers to the US, check whether the vendor is certified under the UK extension to the EU-US Data Privacy Framework; if not, you need the UK International Data Transfer Agreement (IDTA) or the UK Addendum to the EU Standard Contractual Clauses in place with that vendor before sending personal data to them.
This is easy to miss because it's a legal document, not a code change, and it rarely blocks anything technically — the integration just works. But "it works" and "it's compliant" are different questions, and a due-diligence review or a customer's security team will ask for the transfer mechanism by name, not just proof that data is encrypted.
Pre-launch compliance checklist
Before your first paying customer signs:
AyTech note: The safest projects start with a narrow, measurable workflow, then expand after real users prove the value. This keeps budgets controlled and gives Google, buyers, and stakeholders clearer proof of expertise.
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