Tatari operates a media-buying infrastructure connecting brands, agencies, and publishers across connected TV and linear advertising. The tech stack reveals a mature data platform (Kafka, Spark, Airflow, dbt, Databricks, Redshift) paired with modern backend tooling (Kubernetes, GraphQL, TypeScript/React), indicating heavy investment in campaign automation and real-time optimization. Active pain points around data ingestion reliability and sales process gaps suggest the company is scaling operational complexity faster than tooling can keep pace—a common constraint in ad-tech platforms moving from niche to multi-channel.
Tatari builds infrastructure for TV advertising modernization, serving brands, agencies, and publishers managing campaigns across connected TV and linear channels. Founded in 2016 and headquartered in San Francisco with offices in Los Angeles and New York, the company operates a 51–200-person team. The product surface includes campaign execution, network approval workflows, real-time optimization, and inventory cataloging. Sales-led hiring velocity is accelerating, with active openings weighted toward sales (15 roles) and engineering (9 roles), reflecting simultaneous pressure to close deals and scale backend systems handling multi-channel campaign complexity.
Core stack: AWS, GCP, Azure; Kafka and Spark for data pipelines; Airflow and dbt for orchestration; Databricks and Redshift for analytics; Kubernetes and Docker for containerization; Python backend with TypeScript/React frontend; GraphQL for APIs.
Core projects include real-time campaign optimization, linear and streaming TV buys, network approval automation, inventory cataloging, AI-driven automation, and client strategy recommendation systems. Financial modeling and sales performance tools are in active development.
Tatari'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.