Agentic Workload Automation Harness

Closed Pre-Solicitation Posted

Solicitation number
FA8307AI-AWAH
Agency
Responses due
Set-aside
No set-aside

Opportunity facts

Place of performance
San Antonio, Texas 78205, United States

Notice details come from SAM.gov. Updated .

About this opportunity

The Air Force Materiel Command Lifecycle Management Center at Joint Base San Antonio is conducting market research to identify commercially available AI solutions comparable to or exceeding Ask Sage capabilities for secure, scalable generative AI deployment within DoD environments; responses are due by September 1, 2026. This is a Request for Information only and does not constitute a solicitation or commitment to award. Work is performed at Joint Base San Antonio-Lackland, Texas, supporting the Cryptologic and Cyber Systems Division.

The Government seeks solutions providing secure access to multiple Large Language Models, generative AI chat and assistance, document analysis and summarization, content generation, data analysis, workflow automation, Retrieval-Augmented Generation, API integration, and AI-enabled productivity capabilities. Solutions must operate within DoD cybersecurity, data protection, identity and access management, and information-assurance requirements, particularly at Impact Level 2 classification levels. The Government is specifically interested in preventing Government data from being used to train publicly available AI models.

Respondents must document FedRAMP or DoD authorization status, supported deployment models, data handling protections, model availability, technical support, scalability, and licensing structures. Three worksheets are required: alternative solutions comparable to Ask Sage; alignment with capability requirements including natural-language task specification, conversational refinement, autonomous multi-step task execution, tool orchestration, human approval controls, code and terminal execution, artifact creation, and parallel agent execution; and pricing including transition and training costs, monthly or annual plans, volume discounts, and contract terms up to five years. CAGE/DUNS codes and company identification must be provided. NAICS 541512; PSC DA01.

Notice text

The Government is conducting market research to identify commercially available Artificial Intelligence (AI) solutions capable of supporting secure, scalable, and mission-focused generative AI capabilities within Department of Defense (DoD) environments.

The Government is interested in solutions that provide capabilities comparable to or exceeding currently available enterprise generative AI platforms, including Ask Sage. Desired capabilities may include secure access to multiple Large Language Models (LLMs), generative AI chat and assistance, document analysis and summarization, content generation, data analysis, workflow automation, Retrieval-Augmented Generation (RAG), application programming interface (API) integration, and other AI-enabled productivity and mission-support capabilities.

Potential solutions should demonstrate the ability to operate within applicable DoD cybersecurity, data protection, identity and access management, and information-assurance requirements. Respondents should identify applicable FedRAMP and/or DoD authorization status, supported Impact Levels where applicable, deployment models, data handling protections, model availability, integration capabilities, licensing structure, technical support, scalability, and estimated pricing methodology.

The Government is particularly interested in understanding the availability of commercial solutions that provide secure enterprise AI capabilities while protecting Government information and preventing Government data from being used to train publicly available AI models.

This RFI is issued solely for market research and planning purposes. It does not constitute a solicitation, Request for Proposal (RFP), or commitment by the Government to award a contract. Responses will assist the Government in assessing market capabilities, acquisition strategies, potential sources, and commercially available alternatives capable of satisfying the anticipated requirement.

Files

File Type Posted
Agentic Workload Automation Harness.xlsx XLSX spreadsheet

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