Companies are struggling to keep up with compliance regulations and HoundDog.ai‘s AI-powered code scanner aims to solve this problem by preventing personally identifiable information (PII) leaks and automating privacy compliance documentation. In this video, Amjad Afanah, Founder and CEO of HoundDog.ai, discusses the challenges in data security and privacy compliance, and how their solution is helping save companies time and money. He says, “We estimated that just to remediate one issue in production, it takes at least 80 hours of work to go through all of that.”

Introduction to HoundDog.ai’s AI-powered code scanner for detecting PII leaks 

• Afanah discusses the creation of HoundDog.ai and its AI-powered code scanner designed to detect and prevent PII from leaking into logs and third-party systems.
• Afanah talks about his experience as a VP of Product at a data security company, where he noticed the reactive nature of existing data security solutions and how this led him to found HoundDog.ai.

Challenges of data security and privacy compliance

• Afanah identifies two primary issues with data security and privacy compliance: the reactive nature of current processes and tools, and the difficulties in data leak detection and privacy documentation.
• Dealing with PII leaks in production is costly and complex, often involving extensive code changes, log reviews, and compliance reporting. He emphasizes that preventing leaks from the outset is more effective.
• Afanah highlights the labor-intensive and error-prone manual processes many companies use to document data processing activities, underscoring the need for proactive, integrated security solutions.

Potential of GenAI in security and privacy applications

• Privacy and security are typically handled by different teams within organizations, and they can struggle to navigate the growing number of privacy laws and avoid hefty fines.
• Afanah discusses the potential of Generative AI (GenAI) in security and privacy applications. It can struggle with complex tasks like scanning entire codebases for vulnerabilities
• Afanah highlights the different tasks GenAI can excel in such as identifying sensitive data when given specific, simplified tasks. He explains how this application improved their code scanner’s precision rate up to 95%.

The relationship between privacy and security, highlighting customer Juvare

• Afanah discusses the relationship between compliance and security, noting that achieving compliance does not necessarily equate to being secure. Compliance is often treated as a checkbox task rather than reducing data breach risks.
• Security-minded leaders in large organizations prioritize robust security programs, underscoring that compliance should not overshadow the need for effective security practices to prevent data breaches.
• Afanah highlights one of their customers, Juvare, a health tech company providing emergency preparedness software that deals with Protected Health Information (PHI).
• While some customers like Juvare integrate the scanner into GitLab’s CI/CD pipeline, others prefer a single cloud platform to view consolidated issues across all code repositories, file JIRA tickets, and receive alerts via Slack and email.
• Afanah highlighted the ROI, noting that their solution saves significant time and costs by preventing PII leaks and automating privacy compliance documentation, reducing the need for additional full-time employees.
• Afanah discusses the company’s plans following the $3.1 million seed round, saying they will continue to invest in R&D, focus on marketing and sales, and participate in events for security and privacy practitioners.

Guest: Amjad Afanah (LinkedIn)
Company: HoundDog.ai (LinkedIn)
Show: Let’s Talk

This summary was written by Emily Nicholls.