AI-powered supply chain cybersecurity for critical infrastructure and government
Fortress defends critical infrastructure and government agencies against supply chain cyber threats using Python, Kubernetes, and AWS. The tech stack reveals a containerization-first architecture (Docker, Kubernetes, migrating off Ansible) paired with modern observability (Signoz, CloudWatch) and secrets management (actively adopting Vault). Hiring velocity is accelerating across engineering and security roles, while active projects span AI workflow orchestration, CI/CD modernization, and supply chain risk dashboards—suggesting the company is scaling its platform capabilities alongside expanding market reach.
Fortress is an AI-powered cybersecurity company founded in 2015, headquartered in Orlando, Florida, with 201–500 employees. The company serves critical infrastructure operators, government agencies, and their supply chains, focusing on threat intelligence, vulnerability management, third-party risk, and supply chain security (SBOM, vendor risk assessment). The product surface includes supply chain risk dashboards, reporting automation, and audit-readiness capabilities. Engineering and security dominate the hiring mix, with active projects centered on containerized platform deployments, AI-driven workflows, and scalable secure infrastructure.
Python, AWS (Lambda, RDS, ECR, CloudFormation), Kubernetes, Docker, PostgreSQL, React, Node.js, Vault, Jenkins, Terraform, OpenSearch, and Signoz for observability and monitoring.
AI workflow orchestration, containerized platform deployments, supply chain risk dashboards, CI/CD pipeline modernization (blue/green and canary releases), and reporting automation and data models.
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Fortress Information Security's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.