HoundDog.ai provides a proactive, lightweight, and ultra-fast static code scanning solution aimed at preventing PII (Personally Identifiable Information) leaks and ensuring privacy compliance at the code level. Leveraging AI, it continuously detects vulnerabilities that expose sensitive data in various mediums, such as logs, files, tokens, cookies, and third-party systems. In addition to identifying potential data breaches, HoundDog.ai delivers contextual remediation strategies, tracks and visualizes data flows, and automates the generation of Records of Processing Activities (RoPA) for GDPR compliance. It integrates seamlessly with developer workflows, CI/CD pipelines, and popular frameworks such as GitHub, GitLab, and Jenkins.

Secure Agent Augmentation provides a Python SDK and set of helper modules to wrap AI agent tool calls with security controls. It supports integration with popular LLM frameworks like LangChain and Semantic Kernel, and connects to secret vaults (e.g., HashiCorp Vault, AWS Secrets Manager). Encryption-at-rest and in-transit, role-based access control, and audit trails ensure that agents can augment their reasoning with internal knowledge bases and APIs without exposing sensitive data. Developers define secured tool endpoints, configure authentication policies, and initialize an augmented agent instance to run secure queries against private data sources.