Bot, ad fraud and invalid traffic detection for enterprises and ad platforms
HUMAN detects bots, ad fraud and account abuse with a polyglot stack (Go, Rust, C++, Java, JavaScript) and integrations across Cloudflare, Fastly, Akamai and AWS CloudFront, which places its detection close to customer edge traffic. Selenium, Playwright and Puppeteer in the stack point to in-house emulation of automated browsers. Senior-weighted hiring around JavaScript sensors and new detection logic signals ongoing investment in signal collection.
HUMAN is a New York-based security company founded in 2012 that separates legitimate human activity from bots, AI agents and fraudulent automation. Its products cover bot management, invalid traffic detection, ad fraud prevention and account abuse protection for enterprises, advertising platforms and commerce networks. The privately held company employs 201–500 people and hires in the United States, Israel and the United Kingdom. Its data and analytics work runs on Snowflake, BigQuery, Kafka and Elasticsearch, on AWS and Kubernetes infrastructure.
HUMAN uses Go, Rust, C++, Java, Python, JavaScript/TypeScript, React and Node.js, with Kafka, Redis, Snowflake, BigQuery and Elasticsearch on AWS and Kubernetes, plus CDN integrations with Cloudflare, Fastly and Akamai.
HUMAN hires in the United States, Israel and the United Kingdom. Hiring is steady and favors senior engineering, sales and security roles, along with design.
Job posts point to a JavaScript-based sensor for signal collection, new ad fraud detection techniques and detection logic, threat model research, and UX and design system work for the Sightline cyber defense platform.
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HUMAN'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.