Real-time AI Agent Trust Scores with Didit, Fivetran, and dbt

Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.

Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.

This company's pages remain public, but its content is excluded from normalized aggregate trends. Unfiltered raw trends and advanced filtering are available to Accelerate and Lead accounts.

AI agents that approve transactions, onboard customers, or manage access require current and reliable identity and risk information to operate autonomously, and the described approach combines Didit, Fivetran, and dbt to produce dynamic trust scores. Didit supplies verification data such as document checks, liveness results, face matching, AML screening, age estimation, and phone or email verification, while Fivetran automatically replicates this information into a data warehouse to improve freshness, reliability, scalability, and secure handling. dbt then transforms raw verification records through SQL-based, version-controlled, documented, and testable models, allowing organizations to combine signals, retain verification histories, flag inconsistencies or sanctions concerns, and assign scores based on defined business rules. The resulting structured trust data can support AI agents, machine-learning systems, and business intelligence tools, with the goal of enabling more informed and adaptable decisions as users’ behavior and verification status change.

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