Incalmo provides an autonomous cybersecurity platform that continuously monitors network and endpoint activity, using machine‑learning models to detect malicious behavior in real time.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations increasingly depend on digital infrastructure, making them vulnerable to sophisticated cyber threats that require rapid detection and response. Traditional security operations rely heavily on human analysts, leading to delayed mitigation and high operational costs.
Solution
Incalmo offers an autonomous cybersecurity platform that continuously monitors network and endpoint activity, using machine‑learning models to identify malicious behavior in real time. When a threat is detected, the system automatically initiates predefined containment and remediation actions without human intervention, reducing dwell time and limiting damage. The platform integrates with existing security stacks via APIs, allowing seamless deployment across on‑premises and cloud environments. Continuous learning mechanisms update detection models based on new threat intelligence, ensuring the system adapts to evolving attack techniques. By automating both detection and response, Incalmo enables organizations to maintain robust security posture while lowering the reliance on scarce security talent.
Target Audience
Primary customers are mid‑size to large enterprises and managed security service providers seeking to automate cyber defense and reduce dependence on manual security operations.
Features
- Real‑time threat detection powered by supervised and unsupervised machine‑learning algorithms
- Automated response engine that executes containment, isolation, and remediation workflows instantly
- API‑first architecture for integration with SIEM, SOAR, and endpoint protection solutions
- Continuous model retraining using live telemetry and threat‑intel feeds to stay current with emerging attacks
- Scalable deployment across hybrid, multi‑cloud, and on‑premises environments with minimal configuration