A Proactive Approach to Preventing PII Data Leaks and Automating Privacy Compliance Workflows
About Us
HoundDog.ai helps organizations protect sensitive data from exposure and streamline compliance workflows by integrating data security and privacy controls at the code level from the very start. With its AI-powered code scanner, HoundDog.ai detects code logic suspected of handling sensitive data (e.g., PII, PIFI, and PHI), flags vulnerabilities where PII data is exposed in plaintext (in logs, files, and 3rd party systems) and automates the generation of sensitive datamaps and RoPA reports for GDPR compliance. HoundDog.ai supports popular programming languages and integrates with existing tools, CI pipelines and developer workflows.
Our Mission
Empower companies developing applications with sensitive data to proactively prevent leaks of personally identifiable information (PII) in logs, files, or external systems, and to put data mapping exercises for GDPR compliance on autopilot.
The Founding Team
Amjad Afanah
Amjad Afanah is a serial entrepreneur with a rich background in cybersecurity. He led his first company, DCHQ, a cloud management startup, to acquisition, and later founded APISec.ai, which developed one of the first API security scanners. Before founding HoundDog.ai, Amjad served as the VP of Product at Cyral, a data security platform that implements security controls on production data. His experience at Cyral, coupled with significant feedback from security and privacy teams frustrated by the prevalent reactive approach to data security and privacy—which often remains unaligned with evolving codebases—inspired him to start HoundDog.ai.
Joohwan Oh
Joohwan Oh is an experienced engineering leader skilled in both scaling services for millions of users and developing new software from scratch. Before joining HoundDog.ai, he was a founding engineer at Aktos, a FinTech startup focused on modernizing debt collection. Joohwan has also led key projects at prominent companies like Facebook, Amazon, and Instacart. Currently, he oversees the development of HoundDog.ai’s cloud platform and the essential AI workflows that significantly enhance our scanner’s accuracy and coverage.
Sudipta Mukherjee
Sudipta Mukherjee is a recognized authority in static code analysis and has authored several books on the subject. With over twenty years of software engineering experience, he is currently developing patent-pending technologies that power our accurate, efficient, and scalable enterprise code scanner. His recent work has introduced innovative code analysis methods that improve the detection of true positive matches, incorporating interprocedural and taint analysis techniques.
Stop PII Data Leaks at the Source and Automate Data Mapping for Compliance
Through its shift-left approach, HoundDog.ai helps organizations integrate data security and privacy controls from the start. Start for free or book a live demo to better understand the product’s capabilities and pricing.