Dig monitors social video at scale—capturing and analyzing over 90% of brand-related clips worldwide in real-time. The tech stack reveals a mature data pipeline: Python + Elasticsearch + Spark + Airflow/Dagster handling multimodal video ingestion, with React + TypeScript on the frontend and Kubernetes orchestration across AWS/GCP/Azure. The engineering-heavy hiring mix and focus on scalable architecture and cost optimization suggest they're past MVP, now grinding on infrastructure maturity and operational efficiency to support their data-volume problem.
Dig is a social video intelligence platform that helps brands monitor, analyze, and respond to video content across social channels. Founded in 2021 and based in New York, the company decodes billions of video clips to extract spoken words, visuals, products, and captions—surfacing both reputation risks (negative trends, viral crises) and growth opportunities (favorable narratives, competitive insights, product feedback). The platform reaches organizations across brand management, marketing, and communications teams. Dig operates as a lean engineering-driven organization with active development in Israel.
Core: Python, Elasticsearch, Apache Spark, Kubernetes, Docker. Data orchestration: Apache Airflow, Dagster, Flyte. Frontend: React, TypeScript, React Native. Cloud: AWS, GCP, Azure. CI/CD: GitHub Actions, CircleCI, ArgoCD.
New York, United States. The company was founded in 2021 and currently has 11–50 employees.
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