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The objective of this research is to develop a framework to mitigate unexplored and emerging risks that are induced by generative artificial intelligence (GenAI) and related tools in highway construction QA practices. At a minimum, the research shall include: Exploration of the potential misuse of AI tools, such as falsifying and manipulating construction data. Detection of AI-related QA data fabrication and falsification. Mitigation of compromised infrastructure quality.
Starbridge can help you:
Pain points mentioned in board meetings and strategic plans
Instantly outline and draft all requirements
Bring in your USPs and exploit competitor gaps
Starbridge can help you:
Get ahead of RFPs — target accounts planning budget or ending contracts soon
Accounts with contract expirations, meetings mentioning your product, grants, budget changes and more
Starbridge.ai books 30 - 40% of leads into meetings
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Construction quality assurance for the Johnson Canyon landfill module 8 construction project.
Posted Date
Nov 12, 2025
Due Date
Jan 8, 2026
Release: Nov 12, 2025
Close: Jan 8, 2026
Construction quality assurance for the Johnson Canyon landfill module 8 construction project.
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Provide a cloud based learning management system (lms) that includes artificial intelligence (ai) integrations.
Posted Date
Oct 23, 2025
Due Date
Jan 8, 2026
Release: Oct 23, 2025
Close: Jan 8, 2026
Provide a cloud based learning management system (lms) that includes artificial intelligence (ai) integrations.
AvailableThe objective of this research is to develop a guide for state DOTs on how to use AI to enhance transportation data quality. The research will explore and demonstrate how AI can detect, correct, and prevent data errors—automating key aspects of data management. It will identify effective strategies for integrating AI into existing data management practices to enhance the accuracy, consistency, and reliability of transportation and business data systems.
Posted Date
Nov 4, 2025
Due Date
Dec 19, 2025
Release: Nov 4, 2025
Close: Dec 19, 2025
The objective of this research is to develop a guide for state DOTs on how to use AI to enhance transportation data quality. The research will explore and demonstrate how AI can detect, correct, and prevent data errors—automating key aspects of data management. It will identify effective strategies for integrating AI into existing data management practices to enhance the accuracy, consistency, and reliability of transportation and business data systems.
AvailableProvide quality assurance (qa) processes necessary to ensure the accuracy, integrity and fidelity in the administration of assessment tools, and delivery of evidence-based services.
Posted Date
Nov 24, 2025
Due Date
Dec 15, 2025
Release: Nov 24, 2025
Close: Dec 15, 2025
Provide quality assurance (qa) processes necessary to ensure the accuracy, integrity and fidelity in the administration of assessment tools, and delivery of evidence-based services.
AvailableSurface intent from meeting minutes, budgets, and contract expirations. Influence RFP requirements before competitors ever see them.
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