All-in-one HR, payroll, and workforce management for small to mid-market businesses
Push Operations builds an integrated HR and payroll platform for business owners, combining scheduling, time tracking, payroll processing, and compliance tooling into a single application. The tech stack spans PHP, Python, Ruby, and Go across back-end services, with modern front-end tooling (React, Angular, React Native) and emerging AI integrations (AWS Bedrock, CrewAI, RAG). Hiring velocity is accelerating with a 14:11 engineering-to-sales ratio, paired with active projects around payroll platform scaling and back-end API development—suggesting a shift from feature breadth toward infrastructure maturity and compliance robustness.
Push Operations provides HR, payroll, scheduling, and workforce management software designed for small-to-mid-market business owners. The platform integrates payroll processing, labor compliance reporting, time and attendance tracking, and HR operations into a single interface, with POS system integrations for restaurant and hospitality workflows. The company is headquartered in Vancouver, BC and operates with 51–200 employees. Active pain points center on scaling payroll platform reliability, ensuring compliance accuracy, and improving QA processes—core infrastructure challenges typical of a maturing HR-tech platform expanding its customer base.
PHP, Python, Ruby, Go, and C# on back-end; JavaScript, React, Angular, and React Native on front-end. Infrastructure runs on AWS (including Bedrock for AI). Integrations include HubSpot, Salesforce, Zapier, n8n, and Airtable.
Vancouver, BC, Canada. The company actively hires in Canada and the United States.
Push Operations'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.