Secure.com’s AI-driven platform delivers more than simple asset discovery. With ML-powered classification and live attack surface mapping, it gives lean teams 40% better classification and visibility into every asset, identity, and risk, reducing blind spots and enhancing security operations.
Traditional asset discovery stops at raw data. Without context, security teams face blind spots, alert fatigue, and no clear picture of their environment.
Alert Overload
Security teams drown in thousands of raw alerts without prioritization, slowing investigations and delaying response.
Missing Context
Legacy tools list assets but fail to connect relationships, leaving teams without true asset intelligence
Manual Burden
Hours wasted on spreadsheets and scans lead to fading visibility and growing organizational risk.
Asset intelligence is the process of turning raw asset data into meaningful, actionable insights that enhance an organization’s security posture. It starts with the automated discovery of systems, applications, and their interconnections, often using API integrations. Machine learning is then used to classify assets and assess their criticality based on technical attributes and business relevance.
This data is organized into a dynamic, context-aware configuration database that reflects changes in real time. By visualizing the full attack surface—along with misconfigurations, vulnerabilities, and relationships—asset intelligence enables organizations to focus on what truly matters, making informed decisions and reducing risk.
Organizations face "too many tools" and "not enough clarity," leading to "thousands of alerts-and zero clarity." Traditional approaches result in blind spots, misclassification, and reliance on manual tracking.