Automating Data Stewardship for Temporary Account Reconciliation
Description
This AI use case focuses on automating the manual review and verification process for temporary “write-in” accounts submitted by external users within NASA’s agency-wide enterprise Salesforce platform. When users cannot find their organization in the existing institutional database, they submit temporary account records that require data stewards to manually research, validate, and reconcile each entry—often spending up to 50 hours per week. By leveraging AI-driven entity matching, web verification, and metadata enrichment, this solution will significantly reduce manual effort, accelerate the onboarding of new organizations, and improve data accuracy. Automating this process enhances scalability, ensures compliance with data governance policies, and improves the end-user experience across all applications using the enterprise platform.
Detailed example
Deduplication
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Given the large number of individuals and institutions that show interest in collaborating with NASA, we must ensure that records associated with specific entities remain clean, accurate, and traceable in order to enhance our ability to manage partnerships, track engagement trends, and support strategic outreach across the agency. STMD is championing this automation effort to streamline the reconciliation of temporary accounts, which is essential for maintaining the integrity of NASA’s enterprise-wide contact and organization data. This work not only supports STMD’s mission to accelerate the development and adoption of transformative space technologies through broader collaboration but also strengthens the agency’s ability to scale engagement efficiently and responsibly across academia, industry, and government.
Controls / human review
ATO: Not reported; PIA: Not published