This Government Contract opportunity from Department Of Defense was posted on September 30, 2019. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

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DataRobot Software Support

Awarded

M9549419Q0023Federal

Submission Closed09/30/2019, 12:00:00 AM UTC

Contract Overview

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

Active Opportunities Like This One

NAICS: 518210

New

Federal

Intent to Sole Source- London Stock Exchange

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Department Of The Treasury

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W6QK Acc-Apg Contr Ctr

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FedRAMP Cloud Infrastructure & Managed HostingThe FedRAMP Cloud Infrastructure and Managed Hosting subcontract supports prime contractors on Department of State APS projects by providing and managing secure cloud environments. Utilizing AWS GovCloud or Azure Government platforms, the contract ensures a highly available hosting environment with a guaranteed 99.9% monthly system availability. To maintain strict security standards, the provider implements encryption and role-based access controls in accordance with 12 FAM 600. This effort falls under NAICS code 518210 and is managed through Acquisitions - Aqm Momentum for the Department of State, with a response deadline set for November 20, 2026.

Acquisitions - Aqm Momentum

POSTED

1 day ago

DEADLINE

in 23 days

AI Contract Overview

The Department of Defense, specifically the Commanding Officer for the Marine Corps Force Preservation Directorate, issued solicitation M9549419Q0023 for the procurement of DataRobot On-Premise AutoML Base Edition and Enabled Success Package licenses. This initiative aims to revolutionize enterprise analytics by integrating cross-functional research with applied mathematics and social science. By leveraging AutoML tools, the organization seeks to increase its analytic capacity and streamline critical machine learning phases, including feature selection, preprocessing, engineering, model training, and parameter optimization, ultimately providing better data-driven input for resourcing decisions. This brand-name procurement was justified by the requirement for a closed-source solution compatible with the directorate's closed network architecture. The contract structure consists of a base period starting September 30, 2019, with two subsequent option years. The acquisition was conducted as a restricted procurement for authorized DataRobot resellers and evaluated on a Lowest Price Technically Acceptable basis under NAICS code 518210.

General Info

Agency

Department Of Defense → Commanding Officer

Contract Value

$491,400

NAICS

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

Place of Performance

DC, USA

Set-Aside

NONE

Awardee

VERTOSOFT, LLC

Award Issued Date

09/30/2019, 12:00:00 AM UTC

Documents

M9549419Q0023 - On-Premise AutoML and Success Package RFQ

rfq

High

J&A No. 19-009 - DataRobot Software License

justification-and-authorization

Low

AI Contract Breakdown

Uniform Contract Format

Contract not broken down yet

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Timeline

PhaseAwarded

PostedAug 21

Presolicitation

AwardedSep 30

Contract was awarded

Submission Closed

09/30/2019, 12:00:00 AM UTC

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Organization & Contact Information

AgencyDepartment Of Defense → Commanding Officer

Contacts1 person available

OfficeWASHINGTON, DC, 20380-1775, USA

Organization / AgencyDepartment Of Defense → Commanding Officer

Office AddressWASHINGTON, DC, 20380-1775, USA

Contacts

Ana M Cruz ZavalaContract Specialist

contact@example.gov

+1 (555) 000-0000

Full Description

The purpose of this requirement is to enable senior leaders to focus on better outcomes by revolutionizing how enterprise analytics is integrated with cross functional research. This requires a multi-disciplinary approach in bringing together expertise from both social science and applied mathematics to define research questions from motivating problems, gather the appropriate enterprise data, explore the data, build and refine analytic models before providing input for resourcing decisions. In order to increase the capabilities and analytic capacity, FPD seeks to leverage cutting-edge techniques of applied mathematics through the use of AutoML tools, which streamline several facets of the machine learning process that ordinarily require highly trained data scientists. The particular phases of the machine learning and data science application which must be streamlined include: feature selection, feature preprocessing, feature engineering, model training and selection, and parameter optimization.