HoundDog.ai

About HoundDog.ai

HoundDog.ai builds specialized, lightweight code scanners in Rust that deliver fast, deterministic dataflow analysis from your codebase. Two products on one engine. Privacy Code Scanner: shift-left privacy and GDPR data mapping at developer speed. Trace 100+ sensitive data types (PII, PHI, CHD, auth tokens) across code paths into every data sink, including logs, storage, APIs, third-party, and AI integrations. Optional AI analysis on static findings auto-closes false positives, adjusts severities, and adds context; scanning runs inside your CI workflows on cheap CPU, and AI only interprets traces already detected. Companies with custom applications use it to validate privacy reviews conducted in design with code-based evidence before data starts flowing, prevent log leaks, apply proactive AI governance, automate GDPR data mapping, and surface suggested RoPA edits as new categories of personal data and subprocessors emerge. Privacy teams prevent risks instead of documenting them after the fact. Dataflow Context Engine: centralized cross-repo context for AI coding agents. API specs alone don't cover the services and fields consuming your APIs. Without centralized dataflow context, agents burn tokens grepping repos and writing ad-hoc bash scripts to parse code relationships, often on code not checked out locally, leaving AI with an incomplete picture. HoundDog.ai's MCP server and Skills continuously fetch the exact cross-repo context, so prompting your agent to update a service or field runs 5x faster and cheaper, with the full picture of what depends on it. The larger and more complex the codebase, the more valuable it becomes; it thrives where other tools struggle. HoundDog.ai is trusted by Fortune 1000 companies across the technology, finance, and healthcare sectors, and powers Replit's Security Agent to help protect its 45M creators, running 10,000 scans per day to provide deterministic detection of risky data flows and GDPR data maps.