Kenzo offers an Agentic Security Platform that uses AI agents and a unified data mesh to automate security operations. It accelerates threat detection and response by consolidating alerts and telemetry, enabling autonomous investigations and risk-centric alerting for security teams.
Funding
$4.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Security operations teams face significant challenges with alert fatigue, slow detection and response times, and manual, siloed processes. These inefficiencies hinder proactive defense and make it difficult to scale operations effectively against evolving cyber threats.
Solution
Kenzo provides an Agentic Security Platform that modernizes security operations by leveraging a multi-agent architecture and AI-driven analytics. The platform unifies security alerts, context, and telemetry into a proprietary entity-centric schema, enabling a swarm of specialized AI agents to automate defense functions. This approach empowers security teams to accelerate threat investigations, enhance detection engineering, and improve threat hunting capabilities, ultimately reducing risk and increasing operational efficiency.
Target Audience
The platform is designed for security operations teams, including threat intelligence analysts, detection engineers, security analysts, and threat hunters, within organizations seeking to automate defense and accelerate threat response.
Features
- **Agentic Security Platform:** A multi-functional platform built on an agentic AI architecture for comprehensive security operations.
- **Security Data Mesh:** Integrates and normalizes security telemetry from over 150 tools into a unified schema for enhanced analysis and response.
- **Tier 2 AI SOC Analyst:** Autonomously investigates 100% of alerts with dynamic, context-aware playbooks, reducing Mean Time To Respond (MTTR).
- **Agentic Detection Insights:** Provides intelligent rule tuning recommendations and generates new detections from emerging threat intelligence to reduce Mean Time To Detect (MTTD).
- **Identity Risk Engine:** Identifies high-risk users and entities by modeling behavior across multiple data sources and detecting anomalous patterns.
- **Autonomous Investigation:** AI agents dynamically build investigation playbooks on the fly, correlating alerts and context for precise threat remediation.
- **Context-Aware Detection Chaining:** Links seemingly isolated events across users, systems, and time to surface multi-step attack patterns.
- **Risk-Centric Alerting:** Shifts focus from alert-centric to risk-centric methodologies, reducing alert fatigue and prioritizing high-impact threats.