The Context Platform for AI Agents

Super Technologies needed data quality, discovery, and ownership to scale reliably across 800+ professionals, four markets, and a product where data errors are not reporting problems but product failures.

Deployed DataHub Cloud across the full organisation, combining 600+ custom SQL assertions, automated metadata checks, lineage mapping, and a conversational discovery layer that connects every employee to governed, context-rich data.

Caught a live P/L incident before it reached the business, reduced KPI lookup time from an orders-of-magnitude effort to seconds, and gave 200+ employees self-serve access to the answers that once required a data team member to provide.

With 400,000 ungoverned tables and institutional knowledge siloed, Pinterest’s analysts could not trust their data context, making accurate, consistent AI-powered analytics impossible.

Pinterest deployed DataHub as a centralized context platform, combining enforced data governance, AI-generated documentation, and intent-indexed query history into a single context layer that powers its Analytics Agent.

The Analytics Agent became Pinterest’s most-used internal agent: questions that once required hours of exploration now return trusted answers in minutes, with every analyst’s institutional knowledge made accessible to everyone.

Centralized data platforms created bottlenecks in access, governance, and schema standardization across business units

Built ‘Data Forge,’ a decentralized data platform powered by DataHub, enabling secure, self-serve access to trusted data products

Faster time to data for consumers, real-time metadata triggers for automation, and improved data discoverability across teams

Super Technologies needed data quality, discovery, and ownership to scale reliably across 800+ professionals, four markets, and a product where data errors are not reporting problems but product failures.

Deployed DataHub Cloud across the full organisation, combining 600+ custom SQL assertions, automated metadata checks, lineage mapping, and a conversational discovery layer that connects every employee to governed, context-rich data.

Caught a live P/L incident before it reached the business, reduced KPI lookup time from an orders-of-magnitude effort to seconds, and gave 200+ employees self-serve access to the answers that once required a data team member to provide.