Tamnoon provides a managed cloud security remediation platform that combines AI-driven analysis with human expertise to convert security misconfiguration alerts into actionable engineering tasks. The service aims to reduce critical cloud exposure to zero within 90 days, addressing the challenge of overwhelming alert volumes and lengthy resolution times in cloud security management.
Funding
$17.9M 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
Cloud environments generate a high volume of security alerts from multiple CNAPP and CSPM tools, overwhelming security teams and leading to delayed remediation of critical misconfigurations. Traditional manual triage and rule-based prioritization methods struggle to keep pace with the dynamic nature and complexity of cloud infrastructure, resulting in delayed resolution times and increased risk exposure.
Solution
Tamnoon offers a managed cloud security remediation platform that combines AI-driven analysis with human cloud security experts to translate security misconfiguration alerts into actionable engineering tasks. The platform enriches, deduplicates, and prioritizes alerts from various CNAPPs, leveraging AI and machine learning to identify the true cause behind each alert and provide a detailed impact analysis. Tamnoon's cloud security experts validate and execute remediation plans, ensuring that critical cloud exposures are reduced to near zero within 90 days. The service integrates with existing cloud security tools and translates recommendations into verified engineering tasks, which can be carried out by the customer's engineering team or by Tamnoon’s experts.
Target Audience
The primary target audience includes cloud security teams, security engineers, and CISOs who are struggling to manage the overwhelming volume of cloud security alerts and need a scalable solution to reduce their cloud threat exposure.
Features
- AI-powered triage that analyzes and categorizes CNAPP alerts, reducing the workload on security and development teams
- Contextual enrichment of alert data with asset attributes, historical incident data, and threat intelligence feeds
- Cluster analysis that groups related alerts to address interconnected issues holistically
- Operational impact analysis using AI models to streamline the process of analyzing the potential impact of security issues and their remediation
- Dynamic scoring and ranking of alerts based on severity, relevance, asset criticality, and potential impact
- Continuous improvement through feedback from the service delivery team to refine and improve recommendations
- Cross-CNAPP contextual learning that enables the AI to generate configurations automatically based on text and context similarity
- Integration with Wiz, Orca Security, AWS Security Hub, Crowdstrike, Microsoft Defender for Cloud, Sysdig, Lacework, Jira, SentinelOne, GCP Security Command Center, Oracle Cloud Guard, Rapid7, Dome9, Palo Alto Prisma Cloud, Tenable Cloud Security, and GitHub