Inactive Total Small Business Set-Aside (FAR 19.5)

DISCLAIMER: This Request for Information (RFI) is issued solely for market research purposes in accordance with FAR Part 10. It does not constitute a Request for Proposal (RFP), invitation for bids, o... DISCLAIMER: This Request for Information (RFI) is issued solely for market research purposes in accordance with FAR Part 10. It does not constitute a Request for Proposal (RFP), invitation for bids, or a promise to issue an RFP in the future. Responses to this RFI are voluntary; no reimbursement will be made for costs associated with preparing and submitting a response. This RFI does not commit the U.S. Government to contract for any supply or service whatsoever. 1 Purpose The United States Air Force (USAF), Deputy Chief of Staff for Manpower, Personnel and Services (A1), seeks to better understand industry’s capabilities for providing AI-enabled personnel readiness wargaming solutions. The Air Force plans to simulate high- -intensity conflict conditions in order to stress test training and accession pipelines and explore sustainment under high attrition. An artificial- intelligence–enabled Software- as- a- Service (SaaS) wargaming platform will be used to create immersive exercises that adapt to participant decisions and generate realistic adversary actions. AI--enabled wargaming leverages machine- learning- based red- teaming to dynamically adjust to human decisions and uses reinforcement learning and neural networks to mimic adversary decision- making; the Air Force seeks- to harness these capabilities to improve readiness planning. Information obtained through this RFI will inform the Government’s acquisition strategy and future solicitation. 2 Background The Air Force routinely employs wargames to explore future force design and to identify gaps in doctrine, organization, training, materiel, leadership, personnel, and facilities. Traditional wargames rely on static scenarios and manual adjudication. Recent research highlights that AI powered wargaming introduces real- time adaptability, autonomous adversaries and predictive analytics, allowing scenarios to evolve in response to participant decisions. AI--driven red- teaming uses machine- learning- algorithms and neural networks to mimic adversary behavior, challenging participants to develop strategic agility. The Air Force intends to incorporate these innovations into personnel readiness exercises focused on rapid training surge and sustainment under high attrition. 3 Notional Requirement The following description is provided for market research; the final scope may differ. Respondents are encouraged to comment on the feasibility of these tasks, suggest alternatives, and highlight any relevant commercial products or services. 3.1 Scenario 1 – Activation (Scaling the Force) The Government anticipates conducting a series of activities to examine how the Air Force would rapidly expand training and accession pipelines in response to wartime demands: • Planning and preparation: Facilitate a short kick-off session with key stakeholders to align objectives, roles, assumptions, and success criteria for the surge scenario. Deliver an agenda and planning brief. • Baseline analysis and scenario design: Conduct a multiday workshop to analyze current surge capabilities, identify capacity bottlenecks, and design scenario injects. Configure an AI--enabled -wargame platform to host the exercise. • Rapid surge wargame execution: Conduct a one day immersive exercise in which participants respond to a sudden surge in training requirements. The AI platform should dynamically inject events and adjudicate- outcomes in real time. Collect data on participant decisions, system bottlenecks, and performance metrics. • After action- reporting and analysis: Assist Government analysts in organizing data and synthesizing insights from the exercise. Provide methodological guidance and editorial support for a postexercise report. The level of effort for this analytic support is anticipated to require a moderate number of professional hours (e.g., on the order of several dozen hours across planning, data organization, analysis, and report support). Respondents should comment on the amount of effort typically required- for similar projects. • Repayable scenario configuration: Load all scenario content, injects, and adjudication logic into the AIenabled platform to allow the Government to replay the surge scenario or modify it for future exercises. Ensure that the Government retains- ownership of the data generated during the exercise. 3.2 Scenario 2 – Sustainment Under High Attrition A second exercise will explore sustainment of force capability during protracted, high attrition- conflict. Proposed tasks include: • Training and design: Provide a training session (approximately 1–2 days) to teach Air Force personnel principles of immersive wargame design, adjudication frameworks, and how to configure and operate the AI-enabled- platform. • Integrated workshop and exercise: Assist the Government in planning and executing a multiday workshop and immersive exercise focused on sustainment under high casualty and attrition rates. The exercise should allow open- ended moves, AI- driven- adjudication, and collection of qualitative and quantitative data. • After action reporting and analysis: Support Government analysts in organizing data and developing an after- action report. This analytic support will likely require- a comparable level of effort to the surge scenario’s analytic support. • Replayable scenario configuration: Configure the AI platform so the sustainment scenario is replayable and modifiable by the Government without contractor assistance. Provide training materials and documentation to Government personnel. 3.3 Desired Platform Capabilities The Government seeks information on AI-enabled- wargaming platforms that could support the above scenarios. Capabilities of interest include, but are not limited to: • AI driven- scenario generation and adaptation: Ability to rapidly create complex scenarios and adapt them midgame based on participant decisions. Platforms should leverage machine- learning- and large language models to produce realistic injects, narratives, and adversary actions. • Beat System integration: Proprietary Beat System structures the experience into distinct narrative intervals, called beats, that guide participant engagement, decision-making tempo, and AI-driven inject timing. This system ensures a cohesive flow throughout the exercise, supports scalable scenario variation, and makes the simulation more intelligible for injects, after-action analysis, and future reuse. • Internal team communication: The platform must include internal messaging capabilities that enable teams to communicate electronically and asynchronously during gameplay. It should also support direct communication between teams and referees to facilitate clarifications, requests, and decision-making. • In-platform move submission: The platform should allow teams to submit decisions, moves, and actions directly within the system. This functionality should streamline gameplay, reduce administrative overhead, and ensure accurate data capture for adjudication and analysis. • Document upload and distribution: The platform should support the upload of separate documents (e.g., memos, briefings, media, reports) and allow referees or facilitators to distribute them directly to specific participants or teams during gameplay. This enables timely injects, targeted information sharing, and enhanced scenario immersion. • Multi-media immersive environment: Integration of news reports, social media posts, videos, memos and other media into a rich, believable game world. Deep world-building and compelling narratives should make scenarios immersive and engaging. • User accessibility: A low-code/no-code interface that allows users with varying levels of wargaming experience to design and adapt scenarios. Facilitators must retain control over learning outcomes while AI manages complexity and logistics. • Realistic role play and sociocognitive- elements: Ability to immerse participants in realistic roles, using evolving media and social feeds to encourage empathy, reveal tradeoffs, and develop leadership, teamwork and decision- making- skills. • Data capture and analytics: The platform must log all participant activity in structured formats that enable rapid export, review, and analysis. It should support custom tagging, filtering, and metadata generation to facilitate robust after-action reporting. • Replayability and configuration: Allow the Government to save and modify scenarios for future exercises without further vendor intervention. Provide documentation, templates, and configuration files. • Scalability and security: Hosted in a secure cloud environment with compliance to DoD cybersecurity requirements. Ability to operate in unclassified and over time classified contexts (when necessary), with appropriate access controls. • 2-Step Authentication: The platform must include robust two-step authentication (2FA) to ensure secure access and prevent unauthorized usage. At a minimum, 2FA should support time-based one-time passwords (TOTP) through authenticator apps (e.g., Google Authenticator, Clerk, Authy), email or SMS verification for privileged users. The system should allow administrators to enforce 2FA for all users or assign different security levels based on user roles. • Use cases and maturity: Indicate where the platform has been deployed (e.g., academic institutions, government agencies, or commercial clients) and the maturity level of the technology. 3.4 Standards • Realism: Scenario injects generated by the AI should be rated “Realistic” or “Highly Realistic” by a majority of exercise participants in post-exercise surveys. Respondents should explain how they ensure scenario realism and verify AI outputs. • Actionable insights: After action reports should yield insights that are specific, relevant, feasible, and impactful for personnel readiness planning. Describe how your analytic approach converts exercise data into actionable recommendations. • Data ownership: All data generated during exercises will be owned by the Air Force. The contractor must allow data export and must not restrict the Government’s ability to reuse or share that data internally. 4 Information Requested Respondents should submit a Capabilities Statement (maximum 15 pages, excluding appendices) addressing the following items: 1. Company information – Name, address, UEI/CAGE code, primary point of contact, and socio-economic classification (e.g., small business, 8(a), WOSB, SDVOSB). 2. Relevant experience – Description of prior wargaming, simulation, or training projects, particularly those involving AI driven- scenario generation, personnel readiness, or training pipeline analysis. Include contract numbers and customer points of contact where available. 3. Platform description – Technical overview of the AI-enabled- wargaming platform your company offers or would propose. Address the capabilities in Section 3.3, including integration of multi-media content, adaptive scenario generation, user interface, data capture, analytics, security, and replayability. If your platform leverages large language models or other advanced AI techniques, describe them in non-proprietary terms and explain how you mitigate risks associated with AI bias or hallucination. 4. Training and support – Approach to training Government personnel in scenario design, platform configuration, and adjudication. Include training duration, format (in person-/virtual), and materials delivered. 5. Estimated level of effort – High level- estimate of professional labor hours and skill mix (e.g., facilitators, AI specialists, analysts, trainers) required to support activities similar to the surge and sustainment scenarios described. The Government anticipates that design, facilitation, and post-exercise analysis will require a nontrivial but not excessive level of effort (likely tens of hours per scenario), but- seeks industry feedback on reasonable estimates. 6. Pricing models – Typical pricing structures for your services and software (e.g., subscription, firm fixed- price packages, time- and- materials). Provide high- level- cost drivers without quoting specific prices. 7. Risk considerations – Identify potential risks or challenges in delivering an AI-enabled- wargaming solution for the Air Force, such as data security, model accuracy, participant adoption, or scheduling. Offer recommendations to mitigate these risks and to refine the Government’s requirements. 8. Industry day participation – Indicate whether your organization would be interested in attending a virtual or in person- industry day to discuss these requirements. 5 Response Instructions Submission method: Email your response to the Contracting Officer and Contract Specialist identified- in the SAM.gov notice. Use the subject line: “Response to RFI – AI-Enabled- Personnel Readiness Wargaming Support.” • Format: Submit documents in Microsoft Word, Excel, or Adobe PDF. Clearly mark any proprietary or sensitive information. Do not submit compressed or executable files. • Questions: Submit written questions about this RFI to the points of contact within 30 days of posting. The Government may issue an amendment answering questions or scheduling an industry day. 6 Disclaimer This RFI is issued for information and planning purposes only and does not constitute a solicitation. Respondents will not be automatically notified of any future solicitations. Participation in this RFI is not a pre-requisite for participation in any future procurement. Thank you for your interest and we look forward to your response