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AI/ML Readiness Assessment and Implementation

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State & Local

Contract Overview

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

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The AI/ML Readiness Assessment and Implementation subcontract focuses on evaluating and deploying artificial intelligence and machine learning solutions for prime contractors working on City of Phoenix airport projects. The scope of work includes conducting comprehensive readiness assessments of organizational culture, infrastructure, and data quality. Additionally, the selected provider will configure ML models tailored to airport-specific use cases utilizing cloud platforms such as AWS SageMaker or Azure AI and frameworks including PyTorch or TensorFlow. Key deliverables for this engagement include a formal AI Readiness Report and the deployment of operational AI/ML solutions. All personnel involved in the project must undergo background screening. This opportunity is categorized under NAICS code 541511 and is managed by the Aviation agency in Arizona, with a response deadline set for December 3, 2026.

General Info

AI/ML readiness assessment and implementation for City of Phoenix airport projects by December 2026.

Place of Performance

AZ, USA

Set-Aside

NONE

Documents

This scope was carved out of RFQu 26-0072.

The full solicitation package (8 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Airport Technology Consulting Services

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Timeline

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Organization & Contact Information

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AgencyArizona → Aviation
ContactsNo contacts available
OfficeN/A
Organization / AgencyArizona → Aviation
Office AddressN/A
ContactsNo contact information available

Full Description

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Assesses AI/ML readiness and deploys operational solutions for prime contractors on City of Phoenix airport projects. Performs readiness assessments of data quality, infrastructure, and culture; configures ML models for airport-specific use cases using frameworks like TensorFlow or PyTorch and cloud platforms like Azure AI or AWS SageMaker. Requires background screening. Delivers an AI Readiness Report and deployed operational AI/ML solutions.

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