Stellar Cyber, the Full Cycle AI Native SecOps Platform company, announced that it has been named a Top 3 solution in the EMA Top 3 Buyer’s Guide for Extended Detection and Response (XDR). EMA recognized Stellar Cyber as one of the Best for the Mid-Market solutions and also named Stellar Cyber a Top 3 solution for connector breadth, cross-domain telemetry, and coverage gap visibility.
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EMA selected Stellar Cyber because of its open architecture, ability to ingest and normalize telemetry from existing security tools, and AI-driven correlation that helps security teams turn high-volume alerts into high-confidence incidents. For customers, that means faster time to value, stronger visibility across endpoint, network, cloud, identity, and application domains, and better use of the tools they already own.
“Stellar Cyber stood out in our XDR evaluation because it addresses one of the most urgent challenges security teams face today: turning fragmented telemetry and high-volume alerts into actionable outcomes,” said Christopher M. Steffen, CISSP, CISA, CCZT, VP of Research, Information Security, Risk, and Compliance Management at EMA. “Its Full Cycle AI Native SecOps Platform gives organizations broad visibility across existing tools, strong cross-domain correlation, and practical coverage gap awareness without requiring teams to rip and replace their current investments. For mid-market organizations in particular, that combination of openness, AI-driven detection, and operational efficiency makes Stellar Cyber a compelling choice.”
“Security teams do not need more disconnected alerts — they need outcomes,” said Steve Garrison, SVP Marketing, at Stellar Cyber. “EMA’s recognition validates what our customers experience every day: Stellar Cyber helps lean teams improve detection, reduce complexity, and accelerate response without forcing them to rip and replace their existing security investments.”
In the report, EMA noted that Stellar Cyber enriches signals from hundreds of integrated sources, applies AI-driven correlation to surface high-confidence incidents, and uses automated machine learning to learn each customer’s environment and identify behavioral anomalies specific to their infrastructure.
EMA’s evaluation was grounded in analyst expertise, solution assessment, and primary research with senior IT and cybersecurity decision-makers. Its findings reflect the outcomes modern security teams need most: broad integration, complete cross-domain visibility, reduced blind spots, and faster operational response.
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