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Benchmarking and Technical Reporting

Active

Federal

Response Deadline08/31/2026, 04:00:00 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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The Department of Commerce NIST is seeking a subcontractor for a project titled Benchmarking and Technical Reporting. The primary objective is to perform comparative testing between standards-based and AI-assisted integration methods. This scope of work includes conducting stress tests, analyzing data quality, and establishing reliability metrics to determine the effectiveness of each method. The project will culminate in the production of a final technical report containing specific recommendations based on the testing results. This opportunity is associated with NAICS code 541690 and will be performed in Gaithersburg. Interested parties must submit their responses by August 31, 2026.

General Info

NIST seeks a subcontractor for AI and standards-based integration benchmarking in Gaithersburg.

Agency

Department Of Commerce NistView Agency

NAICS

541690 - Other Scientific and Technical Consulting ServicesView NAICS

Place of Performance

Gaithersburg, MD, 20899, USA

Set-Aside

NONE

Documents

This scope was carved out of 1333ND26QNB730516.

The full solicitation package (1 document), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Manufacturing Execution System Development

AI Contract Breakdown

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Timeline

PostedAug 17

subcontract

Response DeadlineAug 31

Submission deadline

Response Deadline

08/31/2026, 04:00:00 PM UTCin 14 days

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Organization & Contact Information

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AgencyDepartment Of Commerce Nist

ContactsNo contacts available

OfficeN/A

Organization / Agency

Department Of Commerce Nist

View Agency Profile

Office AddressN/A

ContactsNo contact information available

Full Description

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Conduct comparative testing of standards-based and AI-assisted integration methods, including stress tests, data quality analysis, and reliability metrics, and produce a final technical report with recommendations.

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