Network security policy automation for hybrid cloud and datacenter environments
AlgoSec automates application connectivity and security policy across hybrid networks using a Kafka-free, distributed tooling approach (Java, Python, Bash) deployed on AWS, Azure, and GCP. Active hiring in engineering (21 roles) and sales (13 roles) reflects simultaneous product acceleration (AI-powered systems, UI/API automation) and regional expansion—a pattern typical of companies moving from policy management into proactive risk remediation at scale.
Notable leadership hires: Sales Director
AlgoSec provides network security policy automation and visibility software for large enterprises managing hybrid infrastructure. The platform discovers applications across multi-cloud and datacenter environments, automates security policy changes, and surfaces compliance risks. Founded in 2004 and based in Ridgefield Park, New Jersey, the company operates with a 501–1,000 person workforce across six countries (United States, Australia, Germany, India, Brazil, Norway). Core customers include mid-market to Fortune 500 organizations running hybrid networks that require faster, policy-compliant application deployment without sacrificing security posture.
AlgoSec runs Java, Python, Bash, and Node.js on Docker, Kubernetes, and AWS/Azure/GCP. Infrastructure code uses Terraform; CI/CD leverages Bitbucket, GitLab, Maven, and Groovy; front-end is Angular/React. Support for Cisco, Palo Alto Networks, Checkpoint, Juniper, and Fortinet appliances.
Ridgefield Park, New Jersey, United States. The company also maintains engineering and sales presence in Australia, Germany, India, Brazil, and Norway.
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AlgoSec'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.