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.

Aladin provides a modular architecture that allows developers to define autonomous agents powered by large language models (LLMs). Each agent can load memory backends (e.g., SQLite, in-memory), utilize dynamic prompt templates, and integrate custom plugins for external API calls or local command execution. It features a task planner that breaks high-level goals into sequenced actions, executing them in order and iterating based on LLM feedback. Configuration is managed through YAML files and environment variables, making it adaptable to various use cases. Users can deploy Aladin via Docker Compose or pip installation. The CLI and FastAPI-based HTTP endpoints let users trigger agents, monitor execution, and inspect memory states, facilitating integration with CI/CD pipelines, chat interfaces, or custom dashboards.