AI-powered omni-channel ad platform for multi-location brands
Eulerity operates a campaign management platform for franchise and multi-location retail brands, unifying paid ads (Google, Facebook, Instagram, YouTube, LinkedIn) with organic channels, call tracking, and review management. The tech stack reveals a development-heavy organization built on TypeScript, React, and Java, with heavy automation tooling (n8n, Zapier) and mobile-first priorities (Android SDK, Jetpack Compose, Kotlin) — suggesting expansion into branded mobile apps alongside web. The hiring velocity is accelerating with 21 roles posted in 30 days, skewed toward engineering and intern-level positions, which aligns with active projects in AI automation workflows and Android app development.
Eulerity provides campaign management software for multi-location brands, franchises, and local retailers operating across paid and organic channels. The platform consolidates Google and Facebook ad spend, review management, local listings, and call tracking into a single interface, along with AI-powered optimization and insights. The company operates from New York with 51–200 employees, hiring across the United States and Canada. Current pain points include scaling demand generation, managing operational complexity across franchise locations, reducing customer churn, and platform reliability.
Frontend: TypeScript, React, Vite, Rollup. Backend: Java. Mobile: Kotlin, Jetpack Compose, Android SDK. Automation: n8n, Zapier. Testing: Cypress, Playwright, Selenium, Appium, Katalon Studio. Ad platforms: Google Ads, Facebook Ads Manager. CRM: HubSpot. Accounting: QuickBooks Online, Xero.
Android app development with AI-first practices, AI-powered automation workflows, smart adaptive interfaces, custom workflow integration for franchise clients, and testing of new platform features and internal procedures.
Eulerity'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.