SYNOPSIS: This Sources Sought Announcement is to assist the US Army Combat Capabilities Development Command - Soldier Center (DEVCOM-SC) Combat Feeding Division (CFD) to identify potential sources to provide systems and tools for data management and predictive models to aid in ration development, manage macro/micronutrient content, and analyze sensory and field test and evaluation data. The goal is to leverage Arificial Intelligence (AI) and/or Machine Learning (ML) to improve data analysis, so that CFD can provide the joint warfighter with products that meet their specific nutritional needs.
The Government requests that responses be submitted electronically to donna.m.glowka.civ@army.mil and gil.cohen.civ@army.mil no later than November 22, 2024 by 5pm EST.
Background: The U.S. Army Combat Capabilities Development Command, CFD is seeking artificial intelligence and/or machine learning algorithms and tools to, aid in ration development, manage micro/macronutrient content, and predict outcomes of sensory and field tests. The combat feeding division develops combat rations with a shelf-life ranging from 18-36 months that provide nutrition in compliance with Army Regulation 40-25 “Nutrition and Menu Standards for Human Performance Optimization” https://armypubs.army.mil/epubs/DR_pubs/DR_a/pdf/web/AR40-25_WEB_Final.pdf At present, many components of rations are discarded due to low acceptability of the products, weight, preparation time, personal preferences, and other factors. If Warfighters do not consume their rations in full, they risk not meeting their dietary needs for optimal performance. This discarding of unwanted products is referred to as ‘field stripping’. Using AI to analyze sensory/acceptability data on the current rations could identify ways to improve combat rations to decrease underconsumption, and waste.
Description: DEVCOM-SC is conducting a Request for Information (RFI) on technologies or capabilities for data analysis to improve development of combat rations for Warfighters.
Specific Specifications:
- Tools and algorithms that leverage AI and ML to aid in ration development and formulation with respect to organoleptic properties (sensory scores), shelf-life, micro/macronutrient content, processing parameters, packaging, ingredient selection, labeling, consumer acceptance, and other relevant properties.
- Interfaces such as Generative AI to aid in ration development. This tool should be able to identify the micro/macronutrient content of ingredients and ration components based on their ingredients and preparation methods.
- AI and Machine Learning tools and algorithms that use readily available data from sensory evaluations and field. This solution would help to predict which ration components would be discarded based on historical sensory and field test data and potential effects on human performance.
- Systems that can manage historical data. This interface would be able to analyze large datasets and give suggestions on how to analyze the data, and provide insights to improve efficiency in ration product development.
Deliverables:
All documentation submitted shall be submitted as MS Word, Adobe PDF, MS PowerPoint, Visio, or MS Excel files.
- Respondents: The White Paper should be written in respondent format, double spaced, and minimum font size of 10 pt. Paper should not exceed 12 pages, including cover sheet.
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- This paper should cover company information (company name, CAGE code, mailing address, and primary point of contact information (to include telephone number and email address).
- The paper should cover the 5 Ws, as applicable. (e.g., What, Where, When, Why and Who. Example focus areas:
- Please discuss any/all relevant current products and services that currently meet or will be able to meet the enclosed requirements.
- Vendors are encouraged to propose alternative products that may be able to meet or exceed the requirements.
- As applicable, please discuss how your product(s) was implemented within industry/Government.
- Please discuss, as applicable, proposed hardware used as part of the solution.
- For Foreign companies: Discuss how the proposer will be able to work with the US Government in the future (i.e., US subsidiary or partner) if required.
- Additional documentation accepted (and not included in the page count for the White Paper) includes, but is not limited to, the following: PowerPoint presentations, Training documentation, product specification sheets, user handbook/guides, pictures, link to demonstrations, test data, etc.
- Test, Certification and Accreditation (C&A) Documentation:
Vendors are requested to provide any supporting documentation illustrating safety certification, government approval, test data, etc.
- Cost:.
Interested parties are invited to submit a response to this Sources Sought Announcement. THIS IS A SOURCES SOUGHT ANNOUNCEMENT ONLY
This Sources Sought Announcement is issued solely for information and planning purposes and to identify interested sources. THIS IS NOT A SOLICITATION. No contract will be awarded from this announcement. This Sources Sought does not constitute a Request for Proposal (RFP) or a promise to issue an RFP in the future. It is subject to change and is not binding on the Government. Further, unsolicited proposals will not be accepted. Funding is not available at this time. The United States Army has not made a commitment to procure any of the items/services discussed, and release of this Sources Sought Announcement should not be construed as such a commitment or as authorization to incur cost for which reimbursement would be required or sought. Response to this Sources Sought Announcement is voluntary and no reimbursement will be made for any costs associated with providing information in response to this and any follow-on information requests. All submissions become Government property and will not be returned.
Not responding to this Sources Sought Announcement does not preclude participation in any future RFP if any is issued. If a solicitation is released, it will be synopsized on the beta.SAM.gov website. It is the responsibility of the potential responders to monitor this site for additional information pertaining to this subject.
RESPONSES:
Interested parties may identify their interest and capability by sending responses regarding this requirement to DEVCOM-SC via e-mail ONLY to donna.m.glowka.civ@army.mil and gil.cohen.civ@army.mil no later than November 22, 2024 by 5pm EST.. The U.S. Government will not pay for any information or administrative cost incurred in response to this Notice. All costs associated with responding to this Notice will be solely at the expense of the interested party.
Please provide business size (indicate your socioeconomic status), applicable NAICS code, and CAGE code. If you hold a GSA Federal Supply Schedule contract, please identify your contract number.
QUESTIONS:
Any questions for clarification may be emailed to donna.m.glowka.civ@army.mil and gil.cohen.civ@army.mil no later than November 18th, 2024 by 5pm EST. Verbal questions will NOT be accepted. Questions shall NOT contain proprietary or classified information. An unattributed list of questions and answers will be published at the same web location of this Sources Sought Announcement.
