Automated Attachment Intelligence for FCC Licensing Systems
Description
The AI system is designed to solve the challenge of extracting and organizing critical information embedded in attachments submitted across FCC licensing systems. Currently, staff must manually search through multiple systems and thousands of documents to locate ownership details and other key data, which is inefficient and time-consuming. The proposed solution automates this process using AI-powered OCR and entity recognition, enabling faster and more accurate access to relevant information.
Detailed example
The AI system outputs structured data extracted from document attachments, including named entities such as company names, individuals, and locations. These entities are categorized, normalized, and stored in a searchable database. The system also supports keyword monitoring, watchlist alerts, and reporting capabilities. Outputs are accessible to authorized FCC staff through integrated tools like Power BI and Power Apps, and are designed to support internal research and analysis workflows.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The AI solution will enhance the FCC’s ability to research telecommunications entities, particularly in support of national security efforts such as identifying foreign ownership and monitoring compliance with the Covered List. It will reduce the time and effort required to compile case materials, improve the accuracy of investigations, and enable faster decision-making. These improvements support the FCC’s mission to protect the communications infrastructure and ensure regulatory compliance, ultimately benefiting the public by strengthening oversight and enforcement capabilities.
Controls / human review
ATO: Not reported; PIA: Not published