Performance advertising platform for insurance and education verticals
Digital Media Solutions operates a performance advertising network connecting high-intent consumers with advertisers in insurance and education. The tech stack—React, Vue, GraphQL, PostgreSQL, Redis, Docker, Datadog on AWS—reflects a modern web application architecture, but the project list reveals significant backend infrastructure work: binlog replication strategy, Kafka stream integration, backup/disaster recovery, and AP automation. Hiring skews finance-heavy (3 of 7 open roles), paired with infrastructure projects, indicating operational scaling challenges around high-volume transaction processing and cost optimization.
Digital Media Solutions operates a lead-generation and performance advertising platform founded in 2012, serving advertisers in insurance (auto, home, health) and education sectors. The company connects consumers shopping for these services with advertisers, generating revenue through return-on-ad-spend performance models. As a public company headquartered in Largo, FL with 201–500 employees, DMS operates a complex, high-volume business model that processes substantial transaction volumes and manages multiple advertising channels. Current operational priorities include scaling accounts-payable infrastructure, improving disaster recovery capabilities, evaluating channel expansion opportunities, and reducing infrastructure costs while maintaining compliance.
Frontend: React, Vue, TypeScript, Tailwind CSS, Webpack, Vite. Backend: Python, Ruby, PHP, Go with frameworks including Django, Rails, FastAPI, Laravel. Data: PostgreSQL, Redis. Infrastructure: Docker, AWS, Datadog, Sentry. Testing: Cypress, Playwright, Selenium.
Active projects include Kafka stream integration, binlog and logical replication strategy, backup and disaster recovery management, AP process automation, expense reporting enhancement, vendor onboarding improvements, and multi-year scenario modeling for capital structure evaluation.
Digital Media Solutions'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.