Kody builds commerce and payments infrastructure for larger businesses with physical locations, running on AWS and GCP with Kubernetes, Kafka and PostgreSQL. A heavy observability and QA layer (Datadog, Prometheus, Grafana, Selenium, Cypress, Appium) lines up with stated pain around payment reliability and legacy-system migration. Hiring is split between engineering and sales, with commercial focus pointed at APAC and enterprise deals.
Notable leadership hires: Director of Engineering
Kody is a privately held company headquartered in Sunnyvale, California, founded in 2018 and sized at 51–200 employees. It offers an AI-native commerce and payments platform, including point-of-sale and smart terminal capabilities, aimed at larger businesses that operate physical venues such as hotels and retail. The company maintains a presence across North America, Europe and Asia Pacific, with current hiring in the United Kingdom, China and Singapore. Its go-to-market combines direct enterprise sales with partnership and referral channels, supported by HubSpot, Salesforce, Intercom and Zendesk.
Kody runs on AWS and GCP with Kubernetes, Docker and Terraform, using PostgreSQL, MySQL, Redis and Kafka, plus Python, Java, Kotlin and JavaScript. Monitoring uses Datadog, Prometheus and Grafana.
Kody is hiring in the United Kingdom, China and Singapore, with roles spanning engineering, sales, product, HR, operations and support, including a Director of Engineering position.
Kody's job posts point to smart terminal integrations, merchant API integrations, an APAC commercial strategy, partnership and referral networks, merchant onboarding, checkout flows and SLO-focused reliability engineering.
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Kody'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.
