Background check and people data platform for trust and safety decisions
Tessera Data operates a people-data and background-check platform built on a modern data stack: Python, Kafka, Apache Spark, Iceberg, Databricks, and Snowflake. The engineering org is scaling cautiously (3 open roles) while operations and sales are expanding faster, suggesting a transition from pure product iteration toward customer delivery and revenue operations. Active projects signal investment in RevOps infrastructure, customer feedback loops, and AI-orchestrated marketing—pointing to a shift from transactional verification toward customer lifecycle management.
Notable leadership hires: Chief of Staff, Customer Success Director
Tessera Data provides background check data and people intelligence for trust-and-safety decisions across online and offline contexts. The company serves organizations that rely on criminal records, alias and address history, driver history, continuous monitoring, and court records to evaluate risk. Founded in 2017 and based in Irvine, California, the company operates across multiple product lines anchored in public records aggregation and verification. Current priorities include improving verification accuracy and speed (addressing high-volume processing), strengthening customer value realization, and building internal technology infrastructure for rapid talent hiring and RevOps maturation.
Tessera Data uses Python, Kafka, Apache Spark, Iceberg, AWS Glue, Athena, Databricks, and Snowflake for data processing; Salesforce, Outreach, and Sales Navigator for go-to-market; and Looker for analytics. They are actively evaluating OpenAI and Anthropic models.
Active projects include an AI-orchestrated customer marketing engine, structured customer feedback collection, RevOps standardization, customer success frameworks, equity and total rewards strategy, and a people technology data architecture to support internal HR operations.
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Tessera Data's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.