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South Carolina Transportation·South Carolina

AI FOR TRANSPORTATION PROJECT COSTING

Closes 9/11/2026$200k – $1MRequest for Information
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Description

The South Carolina Department of Transportation (SCDOT) is issuing an RFI to collect market information on AI‑enabled solutions for transportation project cost estimating. The agency seeks insight into pricing structures, technical capabilities, integration approaches, and human‑in‑the‑loop governance for AI tools that can augment existing estimating workflows across planning, design, engineer’s estimate, validation, and forecasting phases. No contract will be awarded and no payment will be made for responses; the data will support future strategic planning and potential pilot projects. • Desired AI functions include cost prediction, quantity estimation, pay‑item recommendation, unit‑price suggestions, risk analysis, and estimate validation. • Vendors must describe data requirements, integration with SCDOT’s AASHTOWare, GIS, and SQL Server environments, and provide explainable, audit‑ready outputs. • Responses are limited to 35 pages (excluding cover materials), submitted electronically by 5 PM on 11 September 2026, and must be marked for any confidential information.

Attached files

The solicitation documents live at the source — open the bid source above to download them.

Contact

Jeffery C. Schwalk(Procurement Manager)

[email protected]

(803) 737-1018

Key dates

Opened
8/11/2026
Closes
9/11/2026

Last updated

Details

Type
Request for Information
Industry
Information Technology and Software Development
NAICS
541511
Solicitation №
5400030075

Budget estimate

$200,000 – $1,000,000

No dollar amount is disclosed. Based on typical AI consulting and software‑as‑a‑service engagements for state agencies, a proof‑of‑concept or pilot could range from a few hundred thousand dollars to a low‑single‑digit million. Assuming a modest pilot (6‑12 months) at $200‑$500 k and a larger enterprise rollout potentially $1‑$3 M, a reasonable estimate is $200,000 – $1,000,000. Factors influencing the range include the scope (proof‑of‑concept vs. full deployment), licensing model (subscription vs. per‑project), data preparation effort, and integration complexity.

AI estimate from the solicitation

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