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AI/ML Training Data Pipeline & Synthetic Data Generation

Active
Federal

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 contract involves building and managing data pipelines focused on the collection, labeling, and preprocessing of real-world sensor data to support AI and machine learning applications. It also includes the development of synthetic data generation tools aimed at improving the training and robustness of AI models. This work is subcontracted under NAICS code 518210, which pertains to data processing, hosting, and related services. Issued by the Department of Homeland Security's Science and Technology Acquisition Division, the contract was posted on June 4, 2026. Although specific details such as location and point of contact are not provided, the core scope centers on enhancing AI training data infrastructure through both real-world sensor data and synthetic augmentation, ensuring improved model performance and reliability for government applications.

General Info

Build and manage data pipelines and synthetic data tools for AI under Homeland Security contract.

Agency

Department Of Homeland Security → Sci Technology Acq DivisionView Agency

NAICS

518210 - Computing Infrastructure Providers, Data Processing, Web Hosting, and Related ServicesView NAICS

Place of Performance

DC

Set-Aside

NONE

Documents

This scope was carved out of FY26-0107.

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

View the prime solicitation

SETA AI/ML Support Services Extension

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Timeline

Posted

subcontract

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Organization & Contact Information

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AgencyDepartment Of Homeland Security → Sci Technology Acq Division
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Homeland Security → Sci Technology Acq Division
View Agency Profile
Office AddressN/A
ContactsNo contact information available

Full Description

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Build and manage data pipelines for collecting, labeling, and preprocessing real-world sensor data; develop synthetic data generation tools to enhance AI model training and robustness.

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