From CAASM to Asset Intelligence
CAASM made fragmented asset inventories usable. But as security teams hand more decisions to automation and AI agents, an inventory alone isn’t enough. An analyst can pause when records conflict. An automated workflow may act on the wrong asset.
In this report, Software Analyst Cyber Research (SACR) defines Asset Intelligence: a reconciled, current, and traceable layer of asset context that both people and AI-driven workflows can trust at the moment of decision.
The report explores:
Why more connectors and bigger inventories don’t produce trusted context
Why automation and agentic workflows raise the stakes for asset context
The six capability pillars that define Asset Intelligence
A maturity model, from fragmented inventory to just-in-time context for agents and automation
A five-step adoption path for security leaders
How Axonius’s architecture aligns with the model
Download the report to see where CAASM ends and Asset Intelligence begins.
How is Asset Intelligence different from CAASM?
CAASM aggregates, normalizes, and deduplicates asset data into a consolidated inventory. Asset Intelligence builds on that foundation by reconciling conflicting sources, tracking freshness, and adding ownership, identity, and business relationships. It then delivers that context into exposure, control, investigation, and remediation workflows.
Why isn’t a bigger asset inventory enough?
Security tools often make conflicting claims about the same asset. Without explainable reconciliation, source precedence, and freshness tracking, more connectors can produce duplicate tickets, phantom assets, and a distorted view of control coverage.
How should security teams adopt Asset Intelligence?
SACR recommends five steps. Start with a decision under strain, baseline the context quality behind it, define trust requirements, prove one or two operational workflows, then expand coverage and action authority as evidence improves.