Case Study: Matter achieves AI-powered, sub-second sustainable investment insights with Rockset

Matter Uses Rockset to Bring AI-Powered Sustainable Insights to Investors

Matter is a Danish fintech that helps investors evaluate corporate and governmental sustainability across climate, environmental, social and governance themes, ingesting millions of news articles and tracking 20,000+ companies. The company faced slow, hard-to-build analytical queries on schemaless NoSQL stores and an S3-backed data lake; to solve this, Matter adopted Rockset’s cloud analytics platform to auto-ingest S3 data and enable flexible SQL queries over its NLP outputs.

Rockset was integrated as the query layer for Matter’s NLP pipeline—auto-ingesting terabytes of processed news, supporting ad-hoc SQL, the Rockset Write API for manual corrections, and pre-materializing results into DynamoDB for fast delivery. The Rockset-backed architecture let Matter go from months of engineering to being live in days, deliver ~10,000 years of daily sentiment data every second with sub-second latencies, and rapidly add new models and analyses with minimal maintenance.

Matter

Alexander Harrington

CTO