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This Government Contract opportunity from Department Of Commerce was posted on May 19, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

QA/QC & Anomaly Detection System

Closed
Federal

Contract Overview

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The contract involves the development of automated tools focused on identifying data anomalies, monitoring station instability, and detecting processing errors, alongside the generation of quality assurance and quality control (QA/QC) reports. This effort is aimed at enhancing data integrity and reliability through advanced anomaly detection and error tracking mechanisms. The work falls under the NAICS code 541330, which typically relates to engineering services, suggesting a technical and analytical approach to the task. Issued by the Department of Commerce, specifically NOAA, the contract is a subcontract opportunity with a response deadline set for May 29, 2026. The effort is critical for maintaining high standards in data processing and operational stability within NOAA’s systems. Details regarding the physical location for performance or a designated point of contact are not disclosed in the available information. This initiative represents a targeted investment in automation and improved data quality protocols within a government scientific agency.

General Info

Develop automated tools for anomaly detection, monitoring, error reporting, enhancing NOAA data quality.

Agency

Department Of Commerce Noaa

NAICS

541330 - Engineering ServicesView NAICS

Place of Performance

VA

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyDepartment Of Commerce Noaa
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Commerce Noaa
Office AddressN/A
ContactsNo contact information available

Full Description

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Develop automated tools to detect data anomalies, station instability, and processing errors; generate QA/QC reports.