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AI-Enabled Asset Management and Decision Support for Federal Lands Highway

Active

Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The Department of Transportation is seeking to establish an AI-Enabled Asset Management and Decision Support program for the Federal Lands Highway and its seven federal partners. Co-funded by the ITS JPO and Federal Lands Highway, this initiative aims to modernize highly manual engineering workflows by integrating practical artificial intelligence to streamline routine tasks and eliminate operational bottlenecks. Rather than replacing current systems, the project focuses on optimizing the collection and analysis of asset data to transform raw information into actionable insights. This effort is designed to improve multi-agency transportation investments and enhance overall asset management decision-making. The project is categorized under NAICS code 541990 and is currently listed as a forecast. Interested parties may coordinate with point of contact Lisa Randall or Small Business Specialist Ryan Mavis regarding this opportunity.

General Info

DOT seeks AI-enabled asset management to modernize engineering workflows for Federal Lands Highway.

Agency

Department of Transportation

NAICS

541990 - All Other Professional, Scientific, and Technical Services

Place of Performance

AL, USA

Set-Aside

NONE

Documents

0

No documents available

Documents will appear here when they are available.

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Timeline

PostedOct 1

forecast

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Organization & Contact Information

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AgencyDepartment of Transportation

Contacts2 people available

OfficeN/A

Organization / Agency

Department of Transportation

Office AddressN/A

Contacts

Lisa Randall

contact@example.gov

Ryan Mavis

contact@example.gov

Full Description

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Co-funded by the ITS JPO and Federal Lands Highway (FLH), this project establishes an AI-enabled Asset Management program for FLH and its seven federal partners. Currently, FLH engineering workflows are highly manual, limiting data utilization. Rather than replacing existing systems, this initiative integrates practical AI to streamline routine tasks, eliminate bottlenecks, and optimize how asset data is collected and analyzed. This approach transforms raw information into actionable insights, improving multi-agency transportation investments and asset management decisions.

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