Case Study: AdiMap achieves scalable, cost-effective machine-learning financial intelligence and faster time-to-market with Amazon Web Services

AdiMap - Customer Case Study

AdiMap is a data-science company that builds the world’s first financial graph to infer ad revenue, ad spend, app financials, job salaries and related insights across people, companies, jobs, apps and publishers. As a startup it faced high-throughput click-stream processing and large-scale machine-learning needs to extrapolate ad spend and revenues across all ad networks—requirements that would normally demand massive infrastructure, a large systems team, and millions in capital.

AdiMap addressed the challenge by running its platform on AWS—starting with Elastic Beanstalk, then adding Amazon Kinesis for streaming ingestion, Amazon Redshift for petabyte-scale storage, and Amazon Machine Learning for predictive extrapolation from small samples to entire populations. The result was an affordable, highly scalable solution operated by a small team that cut time-to-market, enabled delivery of financial intelligence at scale to major customers, and positioned the company to lower costs further via AWS Lambda and accelerate product front ends with Amazon QuickSight.

AdiMap

Iddo Drori

Founder and CEO