Safety technology platform for fatality prevention in high-risk industries
Forwood Safety builds fatality-prevention solutions for mining, construction, and industrial operations, combining Critical Control Checklists with mobile apps and AI capabilities. The tech stack reveals a modern, distributed architecture—React Native + Node.js + NestJS on AWS—paired with aggressive automation of internal finance processes (Xero, MYOB, payment reconciliation). Active hiring skews senior (6 of 9 roles), concentrated in engineering and sales, suggesting both product acceleration and geographic expansion, particularly into Europe and India.
Forwood Safety is a Brisbane-based fatality prevention specialist founded in 1995, operating across mining, construction, and industrial sectors. The company combines industry consulting with proprietary technology: standardized Critical Control Checklists for major hazards, mobile applications for field teams, and emerging AI-driven predictive capabilities. Their model pairs a consulting division with software products, targeting mid-market and enterprise operators where workplace fatalities remain a material liability. Current execution focuses on European market entry, mobile product adoption in high-risk environments, and internal process automation.
React Native and Expo for mobile; Node.js, NestJS, and GraphQL for backend; AWS (ECS, Lambda, RDS, IAM) for infrastructure; React and Remix for web; Jest, Playwright, and Cypress for testing; Jira and Bitbucket Pipelines for CI/CD.
Australia (headquarters in Brisbane), India, and Italy. Current expansion efforts include implementing solutions across Europe, suggesting active recruitment in that region.
Forwood Safety'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.