Code-grounded GDPR compliance software recognized for replacing survey-based ROPAs and DPIAs with continuous, evidence-based privacy reporting that keeps up with development speed
HoundDog.ai, the privacy code scanning company, today announced it has been named the winner of Best GDPR Compliance Platform in the 2026 Cybersecurity Stars Awards presented by The Hacker News.
“HoundDog.ai builds a code scanner that surfaces how personal data actually moves through applications and integrations, helping privacy teams keep their compliance records aligned with the code they’re shipping,” said the Hacker News judging panel. “It addresses a real gap in how organizations understand and document their data flows.“
For companies that build software applications, traditional workflows for keeping track of processing activities break. Survey-driven ROPAs and DPIAs do not scale: they overwhelm engineering with every release, are inherently inaccurate, and sit quarters behind the codebase. Legacy privacy platforms infer data flows from production after the data is already flowing, miss third-party and AI integrations embedded directly in code, and force teams into documenting risks instead of preventing them. HoundDog.ai’s Privacy Code Scanner closes that gap with privacy reporting grounded in code-based evidence.
What makes HoundDog.ai different is keeping GDPR data mapping aligned with code reality, enabling proactive data minimization instead of reactive cleanup, eliminating blind spots in AI governance and shadow AI, and enforcing privacy by design with code-level evidence under EU AI Act and HIPAA obligations. Privacy teams embed their privacy policies and DPAs as allowlists that flag out-of-bounds pull requests, while new data flows and subprocessors surface as suggested ROPA edits at dev speed. Coverage spans 1,000+ third-party and AI integrations and 100+ sensitive data types.
HoundDog.ai is deployed by Fortune 1000 companies in tech, healthcare, and finance. At a publicly-listed travel management company, the scanner uncovered a number of privacy risks, including excessive log leaks and undocumented subprocessors that had accumulated over the years. It is embedded in Replit’s AI app generation workflow, running 10,000+ daily scans across 45 million+ developers.
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