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This Government Contract opportunity from Federal Communications Commission was posted on September 19, 2024. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

AI/ML Model Development for Document Fraud Detection

Closed
Federal

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The Federal Communications Commission is seeking a subcontractor for the AI/ML Model Development for Document Fraud Detection project to support the Lifeline program. The primary objective is to develop and train machine learning models capable of identifying altered or forged documents, specifically focusing on PDFs and images. The scope of work encompasses critical technical phases including data preprocessing, feature extraction, and the implementation of anomaly detection systems. This opportunity was posted on September 19, 2024, with a response deadline of October 4, 2024. The work is categorized under NAICS code 541715 and is designated for performance in Washington, DC. Interested parties can find further details through the provided government workspace link.

General Info

FCC seeks subcontractor for AI/ML model development to detect document fraud for Lifeline.

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

Place of Performance

Washington, DC, 20005, USA

Set-Aside

NONE

Documents

This scope was carved out of IT-24-140.

The full solicitation package (7 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

USAC RFP: Fraudulent Document Identification Tool

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyFederal Communications Commission → FCC
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Develop and train machine learning models to detect altered or forged documents such as PDFs and images for the Lifeline program, including preprocessing, feature extraction, and anomaly detection.

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