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AI-Based Condition Assessment

Active

International

Response Deadline10/22/2026, 08:00:00 PM UTC

Contract Overview

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

AI Contract Overview

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This subcontract for the City of Saskatoon focuses on the AI-based condition assessment of sidewalk deficiencies. The selected provider will utilize machine learning models, LiDAR, imagery, and geospatial data to identify and measure issues such as spalling, cracking, vertical displacement, and trip hazards. The goal is to generate predictive maintenance recommendations, condition ratings, GIS layers, and comprehensive dashboards for prime contractors. Qualified candidates must demonstrate proven experience in AI-based pavement assessment. The solicitation was posted on September 22, 2026, with a response deadline of October 22, 2026. This project falls under NAICS code 541511 and is managed through the City of Saskatoon's procurement system.

General Info

AI-based sidewalk condition assessment for City of Saskatoon using machine learning and LiDAR.

Agency

City of SaskatoonView Agency

NAICS

541511 - Custom Computer Programming ServicesView NAICS

Place of Performance

CAN

Set-Aside

NONE

Documents

This scope was carved out of 26-0402.

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

View the prime solicitation

2027 Roadway Condition Assessment Program

AI Contract Breakdown

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Timeline

PostedSep 22

subcontract

Response DeadlineOct 22

Submission deadline

Response Deadline

10/22/2026, 08:00:00 PM UTCin 29 days

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Organization & Contact Information

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AgencyCity of Saskatoon

ContactsNo contacts available

OfficeN/A

Organization / Agency

City of Saskatoon

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Office AddressN/A

ContactsNo contact information available

Full Description

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Performs automated identification and classification of sidewalk deficiencies for prime contractors on City of Saskatoon municipal projects. Uses AI and machine learning models to measure cracking, spalling, vertical displacement, and trip hazards. Integrates imagery, LiDAR, and geospatial data to develop predictive maintenance recommendations. Requires proven experience in AI-based pavement assessment. Delivers condition ratings, dashboards, and GIS layers.

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