Security Guardrails for Every Line of AI-Generated Code.

Dam Secure is an AI application security platform that closes the gap between how fast AI coding agents write code and how well that code is actually secured. As development teams increasingly rely on AI agents to author production code, traditional SAST and AppSec tooling — built for a world where humans wrote every line — fails to keep pace. Dam Secure addresses this directly by learning how a team does security from its own existing codebases, then generating and enforcing a set of foundational guardrails tuned to that codebase's specific rules, patterns, and sharp edges.

The platform operates across the full inner loop of the development workflow. It surfaces findings inside the IDE, CLI, TUI, and CI/CD pipelines without requiring new tooling or a separate dashboard. When an LLM or coding agent begins implementing a change, Dam Secure evaluates the code being written against the team's security policies in real time and provides feedback before the code reaches a pull request. For planning stages, it can inject security requirements directly into coding agent context via MCP. At the pull request stage, Dam Secure runs again as part of CI/CD to evaluate changes against defined security requirements and surfaces findings in context.

Dam Secure's distinguishing angle is precision over noise. It is designed to know the difference between a genuine violation and a false positive by grounding every check in the codebase it is protecting, which means teams can trust what gets flagged. The platform targets engineering and security teams that are scaling AI development but cannot afford to have AppSec become a bottleneck — particularly those operating with a high developer-to-security-team ratio and using agentic coding workflows.