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Following Mate’s Series A, CEO Asaf Wiener shares the vision behind the company and why security operations need a new AI-native foundation.
Not all AI SOC Agents investigate with the same accuracy. This article explains how they work, the core capabilities and types that define mature platforms, and why grounding every investigation in an organization's real assets and institutional knowledge is what separates reliable security decisions from generic automation.
Learn how the 6 best AI threat detection tools compare for enterprise SOC teams in 2026. This article breaks them down by the job each does: endpoint, network, SIEM, and AI SOC analyst, then walks through five practical criteria to help you match the right tool to the gaps in your stack.
Learn how agentic SOC platforms use AI agents to investigate every alert end to end, cut response times from hours to minutes, and ground every decision in your organization's own context instead of generic rules.
Learn how to build an incident response checklist that helps security teams detect, contain, investigate, and recover from threats without missing critical steps. Explore checklist types, core components, common challenges, and best practices for improving response speed, consistency, and operational readiness.
Most AI SOC deployments stall because they automate alerts without understanding organizational context. Learn how AI SOC automation works, the architectures and workflows behind it, the metrics that measure its effectiveness, and how it integrates with SIEM, SOAR, EDR, and threat intelligence platforms.
You will hear "context” from every AI SOC vendor. Here's a five-question rubric to tell which ones actually have it, before you write the check.
AI SOC ROI measures the return security teams get from automating triage, investigation, and response, across analyst efficiency, breach cost avoidance, and detection speed. Learn how to measure it with a clear calculation framework, build a leadership-ready business case, and track the metrics that prove value over time.
SOC platforms help security teams reduce alert fatigue, improve investigation efficiency, and scale operations with AI-driven workflows, XDR integration, automated response, and cloud-native detection. Learn how modern SOCs cut false positives, streamline triage, and accelerate threat response with context-aware automation.
The math of defense breaks before Mythos-class capabilities go mainstream. Here's the architecture that survives - and four questions to test if you've built it.
An analysis of modern CI/CD supply chain attacks, revealing how AI-generated variants bypass IOC-based detection and scale mass exploitation.
Detection engineering helps SOC teams cut alert noise, improve threat detection accuracy, and scale security operations through continuous tuning, contextual enrichment, and automated investigations. Learn how modern teams reduce false positives, map detections to MITRE ATT&CK, and accelerate response with AI-driven workflows.
AI SOCs fail without organizational context, leading to generic investigations, false positives, and inconsistent decisions. Learn how Mate Security uses a Security Context Graph to add institutional memory, contextual reasoning, and continuous learning for faster, more accurate, and transparent SOC investigations.
A real-world walkthrough of an Axios supply chain attack, showing how Mate’s AI agents detected, investigated, and contained threats in a CI/CD environment before impact.
Why AI SOC agents fail, and how Mate fixes it. Learn how the Security Context Graph adds context, memory, and reasoning to deliver accurate, consistent investigations.
An introduction to the Security Context Graph, Mate’s data model that gives AI SOC agents real context, improving accuracy, consistency, and trust in investigations.
Mate Security is now available on AWS Marketplace, enabling faster procurement and deployment of its AI SOC platform while delivering measurable improvements in efficiency and response times.
Mate Security joins the 2026 CrowdStrike, AWS & NVIDIA accelerator to advance AI-powered SOC innovation and scale next-generation cloud security solutions.
A simulated React2Shell attack from a SOC perspective, revealing early weak signals, exploitation, and how RCE unfolds in real environments, plus detection and prevention insights.
18 popular npm packages were compromised to hijack crypto transactions. Learn how to detect exposure, secure CI/CD pipelines, and quickly remediate affected dependencies.
What SOCs can learn from elite soccer teams: coordination wins. Discover how better tool integration, shared context, and teamwork can reduce noise and improve security outcomes.
Why autonomous SOCs fail, and how to fix it. Learn why human-AI collaboration, not full automation, leads to better detection, smarter investigations, and stronger security outcomes.
Turn false positives into an advantage. Learn how antifragile SOCs use benign alerts, missed threats, and recurring incidents to continuously improve detection and stay ahead of evolving threats.
Detection exclusions create hidden security gaps. Learn how static exceptions lead to “Swiss cheese” defenses, and why dynamic context is key to reducing noise without increasing risk.
AI automation makes old security metrics obsolete. The real ROI comes from beating attacker speed, stopping kill chains, detecting novel threats, and reducing business risk.
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