This platform uses AI to analyze existing security telemetry, providing actionable insights into cyber coverage across assets, identities, and networks. It helps organizations identify redundant tools and coverage gaps to rationalize security spend and strengthen their overall security posture. The service delivers architectural clarity by mapping controls to business-critical assets, supporting initiatives like Zero Trust implementation.
Funding
$2.9M 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
Organizations struggle to identify and prioritize their most critical assets within complex IT environments, leading to inefficient allocation of cybersecurity resources and increased risk of breaches. Traditional asset management approaches often rely on manual surveys, agent deployments, and network scans, which are time-consuming, incomplete, and difficult to keep up-to-date. This lack of visibility into business context hinders effective vulnerability prioritization and threat exposure management.
Solution
KeyCaliber offers a Continuous Threat Exposure Management (CTEM) platform that automates asset discovery, categorization, and criticality scoring by leveraging existing security logs and telemetry. The platform employs machine learning models to analyze asset behavior and infer business context, providing organizations with a comprehensive view of their high-value assets and potential attack pathways. By identifying security coverage gaps and overlaps, KeyCaliber enables security teams to optimize resource allocation, prioritize vulnerabilities based on business risk, and reduce the likelihood of breaches. The platform integrates with existing security infrastructure without requiring agents, scanners, or SPAN ports.
Target Audience
KeyCaliber targets enterprises, managed service providers (MSPs/MSSPs), cyber insurance companies, and cyber consulting firms seeking to improve their cyber risk management, vulnerability prioritization, and asset management capabilities.
Features
- Automated asset discovery across cloud, on-premises, and unmanaged (shadow IT) environments
- Machine learning-based criticality scoring that assigns business impact scores to each asset
- Visualization of asset connections and potential attack pathways
- Identification of security coverage gaps and overlaps to optimize security tool deployment
- Risk prioritization based on business impact and potential exploitability
- Integration with existing security logs and telemetry data sources
- Agentless architecture that minimizes deployment overhead and operational complexity