Cybersecurity startup Mate has emerged from stealth with a $15.5 million seed round as it looks to overhaul how Security Operations Centers operate. Backed by Team8 and Insight Partners, the company is pitching an AI-native approach that turns reactive SOCs into continuously learning defense engines. The new capital will fund product scaling, deeper work with design partners, and preparations for a broader enterprise rollout.
Market Context
Security teams are drowning in data, alerts, and fragmented tools, and the traditional answer of adding more dashboards is clearly hitting a wall. Research from Devo indicates that a large majority of analysts feel overwhelmed by alert volumes, false positives, and a lack of meaningful context to guide decisions. Many also report spending considerable time manually gathering and stitching evidence before they can even decide whether an alert matters, all while CISOs struggle with persistent talent shortages and rising threat exposure.
Mate’s AI-Driven SOC Platform
Mate is designed to plug into the systems SOC analysts already rely on, including SIEM platforms, endpoint detection and response tools, and email security solutions. From day one, the platform begins to learn from an organization’s best analysts, capturing their investigative patterns and institutional knowledge in real time. Powered by large language models, reasoning engines, and specialized AI agents, Mate automatically investigates alerts, connects disparate pieces of evidence, and either resolves issues with full documentation or escalates complex incidents with rich context.
Early Traction and Use Cases
In early enterprise pilots with financial institutions and critical infrastructure operators across the United States and Europe, Mate reports significant reductions in mean time to respond. SOC teams using the platform have been able to cut hours lost to false positives while expanding coverage without adding headcount at the same pace. Over time, each alert investigated feeds a growing knowledge base, which Mate’s agents use to deliver investigations at the depth and accuracy large enterprises require, making human analysts as much as ten times more effective.
Backing Investors and Strategic Vision
For CISOs dealing with fast-evolving threats and tight budgets, Mate’s backers argue that AI-driven operations are moving from experiment to necessity. Team8 Capital partner Ori Barzilay describes Mate as evidence that AI in security operations is no longer a distant trend but an immediate transformation, noting that SOC teams are racing to embed AI into their workflows. He points out that attackers are already using AI to scale their campaigns, and that the only sustainable defense is to scale SOC capabilities and arm analysts with powerful AI agents, a role Mate aims to fill.
Founding Team and Company Outlook
Mate was founded in early 2025 by a team with deep roots in cloud security and large-scale threat operations. Chief executive officer and co-founder Asaf Wiener previously held product leadership roles at Wiz and Microsoft and is the first Wiz alumnus to launch a startup, while co-founder Oren Saban served as head of product for Microsoft Defender XDR and Security Copilot. They are joined by co-founder Guy Pergal, a veteran of Microsoft’s threat intelligence center and former engineering leader at Axonius, giving the company a leadership bench that has already helped build security products used by thousands of teams worldwide.
Mate positions itself as an AI-first SOC platform that converts the experience of top analysts into a constantly improving defensive layer for modern enterprises. By embedding directly into existing security stacks and automating much of the investigative grind, the company is targeting both the efficiency crisis in SOCs and the growing mismatch between attacker and defender capabilities. With substantial seed backing and a seasoned founding team, Mate is betting that continuously learning, AI-driven security operations will become the new default for organizations facing escalating cyber risk.