

The future of detection requires a new approach: alerts enriched by unified threat intelligence and extended internal telemetry, including non-security data, that more accurately reflect business risk.
Traditional security telemetry served us well, but it's inherently limited. It focuses on predefined data points, often missing the broader context that could signal a threat. As Christian Karam, Anomali Senior Advisor and former Deputy CISO at UBS, explains:
"For the last 30 years, the whole security industry operates within a universe of, let's say, 40, 50 different kinds of security telemetry. Telemetry on the endpoint, on the network, on the identity. That’s the universe of toys that you can work with."
That narrow telemetry universe often means detection efforts are siloed, missing the full picture of how external threats map to internal activity.
Modern detection demands more than traditional log analysis. Christian notes the importance of bringing in telemetry that goes beyond classic sources, including operational and behavioral data.
"You can now ingest non-standard security telemetry or non-security telemetry and then bring it in as an extended telemetry that tells you a different story about your environment and how you operate," he explains.
This extended telemetry allows organizations to correlate threat intelligence — indicators of compromise (IoCs), tactics, techniques, and procedures (TTPs), and threat actor behavior, with internal data in real time. The result is enriched alerts that tell you if what’s “out there” matches activity in your environment.
Artificial intelligence (AI) plays a critical role in this evolution. By analyzing and correlating massive volumes of diverse telemetry, AI helps security operations center (SOC) analysts surface threats that would otherwise be missed. As Christian puts it:
"AI sitting next to a very well-trained SOC analyst or security analyst is like having a great business generalist that can kind of guide you into understanding what's happening on the business side."
AI enables organizations to move from collecting logs to making fast, confident decisions based on meaningful signals.
As these enriched alerts replace raw logs, the industry is shifting from systems of record to systems of action. The goal is not to gather more data. The goal isso unify the threat intelligence and telemetry you already have and drive real outcomes. Detection and response become faster, more accurate, and more aligned with the way your business operates.
Analysts and security leaders are increasingly aligned on this shift. According to a Forbes Technology Council article: “A security platform that coalesces multiple streams of contextual data with various forms of detection enables organizations to reduce the time needed for threat detection and response.”
This is where AI becomes essential. More than just automating detection, AI can enrich signals across those diverse data streams. A 2025 report found that 70% of cybersecurity professionals say AI is highly effective at detecting threats that would previously go unnoticed.
Together, these perspectives reinforce a unified approach: AI-powered platforms that merge threat intelligence, extended telemetry, and business context to deliver fast, actionable insights.
Anomali redefines detection by unifying the world’s largest repository of curated threat intelligence, Anomali ThreatStream, with a modern, cloud-native SIEM. A scalable data lake gives you complete access to your data, not just summarized alerts.
With Anomali, organizations can:
With Anomali, security teams don’t just monitor activity — they get full context, so they can respond instantly. That’s the Anomali difference.
See how Anomali fuses threat intelligence and telemetry to deliver enriched alerts aligned to your business risk. Schedule a demo.
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