In this episode of Compliance Technologies, we continue the SOC 2 series by focusing on the Security Trust Service Criteria and why, in SOC 2, security is not the end goal, but the baseline.

Rather than treating security as a collection of tools or policies, this episode explores how SOC 2 evaluates whether security is operationally enforced through systems and infrastructure. We discuss why manual controls, screenshots, and one-time efforts don’t scale, and how consistent, system-driven enforcement is what SOC 2 actually expects.

This conversation reframes security as something systems quietly do every day, not something teams scramble to demonstrate during an audit window. It also highlights why many SOC 2 challenges are architectural rather than procedural.

If you build, operate, or oversee systems that handle sensitive data, this episode will help you understand what SOC 2 is really asking when it evaluates security and why reliability matters more than heroics.

In this episode of Compliance Technologies, we begin a new series on SOC 2 by stepping back from checklists and reports to ask a more fundamental question: what does trust actually mean in modern systems?

SOC 2 exists because trust no longer scales through policies, promises, or good intentions alone. As systems grow more complex, trust becomes something that must be demonstrated through infrastructure, automation, and consistent behavior.

This episode explores why SOC 2 emerged, what it is really trying to measure, and how it quietly assumes that trust is a property of systems , not statements. Rather than treating SOC 2 as an audit exercise, we frame it as a reflection of how organizations operationalize security, reliability, and responsibility at scale.

If you build, operate, or oversee systems that others depend on, this conversation sets the foundation for understanding SOC 2 beyond the report and into the way trust is actually engineered.

In this episode of Compliance Technologies, we bring the GDPR series together by focusing on the principle that ultimately connects everything: accountability.

After exploring privacy by design, data minimization, purpose limitation, data retention, and lawful basis, this episode explains why GDPR enforcement increasingly centers on one core question: can an organization demonstrate compliance in practice, not just on paper?

We discuss how accountability shifts compliance from policies and intentions to systems, architecture, and evidence, and why regulators now expect organizations to continuously prove how their data processing decisions align with GDPR principles.

This episode reframes accountability as the real requirement behind GDPR, one that exposes inconsistencies between design choices, operational behavior, and compliance claims.

If you build, operate, or govern systems that process personal data, this conversation will help you understand what regulators are truly evaluating when they assess compliance.

In this episode of Compliance Technologies, we continue our series on GDPR fines by unpacking one of the most commonly misunderstood topics in data protection: lawful basis and consent.

GDPR requires that every instance of personal data processing have a clear and appropriate lawful basis. While consent is often treated as a default justification, it is also one of the most fragile, especially when systems cannot properly handle withdrawal, purpose changes, or downstream data use.

We explore why "we have consent" is often not enough, how organizations misuse consent when other lawful bases may be more appropriate, and why lawful basis should be treated as a system-level design constraint, not just a legal checkbox.

This episode reframes lawful basis as something systems must actively enforce, track, and respect over time.

If you build, operate, or oversee systems that process personal data, this conversation will help you understand where compliance claims often break down, even when intentions are good.

In this episode of Compliance Technologies, we continue our series on GDPR fines by examining one of the most enforceable compliance risks: data retention.

GDPR requires organizations to keep personal data no longer than necessary for the purpose it was collected. In practice, many systems retain data indefinitely through backups, logs, analytics pipelines, and downstream services, long after its original purpose has expired.

We explore how retention failures emerge, why deletion and anonymization are engineering challenges rather than policy problems, and how excess data quietly compounds regulatory and security risk over time.

This episode reframes data retention as a system lifecycle issue, where compliance depends on a system’s ability to let go, not just to collect.

If you build, operate, or govern systems that process personal data, this conversation will help you spot where retention risk often hides in plain sight.

In this episode of Compliance Technologies, we continue our series on GDPR fines by exploring one of the most subtle and most commonly violated principles in data protection: purpose limitation.

GDPR requires that personal data be collected for explicit, specific, and legitimate purposes, and not quietly reused in ways that are incompatible with the original intent. In practice, many systems change over time, repurposing data for analytics, monitoring, or AI without clear reassessment.

We discuss how purpose change happens, why internal reuse still carries compliance risk, and how modern data pipelines and AI systems amplify the challenge. This episode reframes purpose limitation as a governance and architecture problem, not just a legal or consent issue.

If you build, operate, or oversee systems that process personal data, this conversation will help you see where compliance risk often accumulates even when everything appears to be working.

In this episode of Compliance Technologies, we continue our series on GDPR fines by focusing on one of the most misunderstood principles in modern compliance: data minimization.

GDPR requires organizations to collect personal data that is adequate, relevant, and limited to what is necessary. In practice, many systems do the opposite, collecting data “just in case,” for analytics, future features, or convenience.

We explore why this mindset has become a growing compliance risk, how unnecessary data quietly turns into legal exposure, and why regulators increasingly view excessive data collection as a design failure rather than an operational mistake.

This episode reframes data minimization as a system architecture problem, not a documentation exercise, especially in environments involving analytics, monitoring, and AI.

If you build, operate, or govern systems that process personal data, this conversation will change how you think about what your systems collect and why.

In this episode of Compliance Technologies, we launch a new series focused on real-world compliance incidents, starting with GDPR fines.

We examine one of the most significant GDPR enforcement actions to date: the €345 million fine imposed on TikTok by Ireland’s Data Protection Commission. This case wasn’t about a data breach or a cyberattack, it was about privacy by design and by default.

We discuss how default product settings, especially for minors, became a compliance failure, why offering privacy options is not enough under GDPR, and how architectural and UX decisions quietly turn into regulatory risk.

This episode highlights a critical shift in compliance enforcement: regulators are no longer only auditing policies and procedures, they are auditing systems, defaults, and design choices.

If you build or operate systems that process personal data, this conversation is for you.