Collate builds a semantic metadata platform where AI agents automate data governance tasks—classification, documentation, lineage mapping—at scale. The stack reveals a dual-mode architecture: Python + Java + Node.js/React for the agent engine and UI, plus integrations across Snowflake, Databricks, and BigQuery for data system connectivity. The company is actively operationalizing its AI agent layer while hardening SaaS observability and CI/CD reliability, suggesting a shift from metadata-catalog-as-software toward AI-as-the-governance-interface.
Collate provides a semantic intelligence platform that connects metadata, context, and meaning across fragmented data environments. The product sits on OpenMetadata (an open-source metadata standard) and layers AI agents on top to automate data management workflows—discovery, governance, classification, documentation enrichment. It serves data teams and organizations building modern data stacks on cloud warehouses like Snowflake, Databricks, or BigQuery. Current projects focus on operationalizing agent workflows, reducing customer time-to-value, and building observability for SaaS instances. The team is based in Saratoga, California.
Java, Python, Node.js, and TypeScript for core services. React for UI. Deployed on AWS, Azure, and GCP with Kubernetes and Docker. Integrates with Snowflake, Databricks, BigQuery, and runs on OpenMetadata.
Operationalizing AI agents for data governance, accelerating customer time-to-value, maturing data practices, hardening the OpenMetadata SaaS platform, and building observability for SaaS customers.
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