Homegrown AI Apps

Homegrown AI applications are developed internally to improve productivity, automate business processes, and deliver better customer experiences. They can retrieve enterprise data, connect to internal APIs, external tools, plugins, MCP servers, SaaS platforms, and business systems, and execute actions or trigger workflows. This introduces risks such as prompt injection, sensitive data leakage, insecure integrations, compliance violations, and excessive agency. Traditional application security tools aren't designed to address these AI-specific security challenges, which require continuous visibility, governance, and security throughout the application lifecycle.