JSC SMA NT Paper WAD Data Extraction · Federal AI Intelligence

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: Yes (prohibited by law)Source: c) Yes – disclosure is prohibited by law

Mission

Topic area: Science
Operational functions: Document processing and extraction Derived by keyword rules; see methodology

Problem the AI is intended to solve

This application aims to provide the Quality Flight Equipment Division with a strong paper Work Authorization Document (WAD) data extraction capability using AI models. The data inputs include scanned PDF versions of original paper Work Authorization Documents (WADs) stored in the QFED data center. This application will be leveraging Google's Gemini Pro models to accomplish this effort. Users will be able to query critical quality-based information from large numbers of WADs to better understand Task Performance Sheet and Discrepancy Report execution trends and areas for improvement.

Expected benefits

This application aims to provide the Quality Flight Equipment Division with a strong paper Work Authorization Document (WAD) data extraction capability using AI models. The data inputs include scanned PDF versions of original paper Work Authorization Documents (WADs) stored in the QFED data center. This application will be leveraging Google's Gemini Pro models to accomplish this effort. Users will be able to query critical quality-based information from large numbers of WADs to better understand Task Performance Sheet and Discrepancy Report execution trends and areas for improvement.

System outputs

Information on scanned PDF documents.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported