AI Scheduling Tool
*****Thie requirement has been revised, please see below***** This Sources Sought Notice is for Market Research ONLY to determine the availability, capability and interest of small business firms for ... *****Thie requirement has been revised, please see below***** This Sources Sought Notice is for Market Research ONLY to determine the availability, capability and interest of small business firms for a potential small business category type set-aside. NO AWARD will be made from this Sources Sought Notice. NO SOLICITATION, SPECIFICATIONS, OR DRAWINGS ARE AVAILABLE AT THIS TIME as this is solely for Market Research. Please do not request such documentation. Requests for any of this information will go unanswered. If the conditions at FAR 19.502-2(b) are met the contracting officer is required to set the acquisition aside for small business concerns. Interested contractors who have the skill, capabilities, and workload capacity to complete the project described are invited to provide their capability statements to the point of contact listed below. All responses will be used to determine the appropriate acquisition strategy for a potential acquisition. The purpose of this notice is to obtain a snapshot of current market capabilities and gain knowledge of potential small business sources to include small business in the following socioeconomic categories: Certified HUB Zone; Woman-Owned Small Business (WOSB) and Serviced-Disabled Veteran-Owned Small Business (SDVOSB); Veteran Owned Small Business (VOSB) and 8(a) small business concerns who can provide an Artificial Intelligence (AI) scheduling tool to augment current practices in predictive schedule analysis. Other than small businesses are encouraged to express interest and submit capability statements as well. Contractors’ capabilities will be reviewed solely for the purpose of determining an appropriate acquisition strategy to include whether this prospective action is appropriate to be set-aside for the small business community or should proceed as an unrestricted full and open acquisition. Other than small businesses are encouraged to respond to this NOTICE to provide a greater context of current market capabilities. However, per the Federal Acquisition Regulations, preference will be given to the small business categories as listed above. In determining the acquisition strategy, the Government must ensure there is adequate competition among the potential pool of available contractors. The Government estimates issuing a solicitation in mid-to-late February. The Government intends to award Firm-Fixed Price Purchase Order. The NAICS Code is 513210 (Software Publishers). The size standard is $47M. Product Service Code is DA10 IT and Telecom – Business Application/Application Development Software as A Service. SUMMARY OF REQUIREMENT: The U.S. Army Corps of Engineers (USACE) – Sacramento District (SPK) is seeking sources for an Artificial Intelligence (AI) construction scheduling tool. The Government requires an existing Commercial-Off-The-Shelf (COTS) or Software-as-a-Service (SaaS) product capable of forecasting construction schedule risk and augmenting project teams in the development of risk-mitigation scenarios. The core of the solution must be a predictive AI model that is pre-trained on a large and diverse dataset of historical construction projects. This model must be able to ingest standard construction scheduling files (e.g. Primavera P6, Microsoft Project) and quantify potential schedule delays or opportunities. Furthermore, the tool must feature a conversational user interface (e.g., a Large Language Model chatbot) that allows users to ask questions about schedule risk, understand drivers of that risk, and interactively model the impact of potential mitigation strategies. The solution must be a mature, existing product ready for rapid deployment and cannot be developmental in nature or require Government data to train its predictive models. Finally, the contractor must provide a representative point of contact for initial user training and technical support for the duration of the contract. TECHNICAL REQUIREMENTS: Software must use a predictive AI model to forecast construction schedule risk by quantifying potential delays or opportunities (e.g., providing a predicted range of completion dates, probability of delay) at the activity and/or work-package level. Software must include conversational user interaction (LLM-enabled) to explain drivers of risk, answer user questions about the construction schedule, and support iterative mitigation planning. The software’s predictive capability must be delivered as an existing commercial product (COTS/SaaS) that is operational at time of award and provides meaningful results without requiring USACE data for model training. The predictive model must be pre-trained on a historical construction project dataset spanning multiple construction sectors (including vertical and horizontal) with a minimum collection size of 100,000 distinct and diverse projects from a wide range of project types, contract values, and geographical locations. Software must support ingestion of common construction scheduling and project formats. This shall include, at minimum: - Core Scheduling Formats: Primavera (.xer, .xml) and Microsoft Project (.mpp) - Contextual Document and Data Formats: Support for common formats like .pdf, .docx, .xlsx, .csv, and .txt for use in contextual analysis Software must allow the upload of project-relevant administrative/reference documents (e.g., specifications, regulatory guidance). The conversational interface must be able to reference the content of these uploaded documents to provide context-aware answers to user questions. The product must provide logical data isolation such that USACE/SPK uploaded schedules and documents remain segregated from other customer data. USACE data shall not be used to train or fine-tune contractor’s model(s) without explicit written authorization. The product must be capable of being fully provisioned for new users within 10 business days of a contract award or notice to proceed. CAPABILITY STATEMENT The following requests are designed to inform the US Army Corps of Engineers, Sacramento District, of current service contractor market capabilities. Please provide your response to the following. The submission is limited to 10 pages. 1) Offeror's name, CAGE Code, address, point of contact, phone number, and e-mail address. 2) Offeror's experience and capability to complete contracts of this complexity and comparable work performed within the past 2 years. Describe the Prime’s self-performed effort, brief description of the project, customer name, timeliness of performance, customer satisfaction, and dollar value of the project. 3) A description of the dataset used to train the predictive model, including the approximate total number of distinct historical construction projects (e.g., 10k–50k; 50k–100k; 100k–250k; 250k+) and a summary of the construction sectors, project types, and geographic regions represented in the dataset. 4) A statement on the offeror’s standard timeline (in business days) to provision new accounts following a contract award, including a description of the typical onboarding process. 5) Offeror's socioeconomic type and business size (Certified HUB Zone; Woman-Owned Small Business (WOSB) and Serviced-Disabled Veteran-Owned Small Business (SDVOSB); Veteran Owned Small Business (VOSB) and 8(a) small business concerns). The Capabilities Statement will not be considered an offer (proposal) or a bid for any future Request for Quotes/Proposal that may result from this notice. Moreover, it will not restrict the Government to an ultimate acquisition approach. This notice is for information and planning purposes only. The respondents will not be notified of the results of any review conducted of the capability statements received. Please notify this office in writing via email by February 18, 2026 at 11:00am PST. Submit response and information through email to: Lachad.c.jefferson@usace.army.mil. Please include Sources Sought No. W9123826S0008 in the subject line.
Data sourced from SAM.gov.
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