Sources Sought : Commercial Space Domain Awareness ( SDA ), Training Large Language Model ( LLM ) Module

2026-11-03

PURPOSE / DESCRIPTION1 . THIS IS A SOURCES SOUGHT ANNOUNCEMENT ONLY . This notice does not constitute a commitment by the Government . All information submitted in response to this announcement is voluntary , and the Government will not pay for information requested nor will it compensate any respondent for any cost incurred in developing information provided to the Government . The Government is under no obligation to acknowledge receipt of submissions or of the information received , or to provide feedback to respondents with respect to any information submitted under this announcement . 2 . This Sources Sought seeks information on commercially available large language model ( LLM ) trainers capable of ingesting user inputs and technical documentation to create and update training as the needs of the operational system changes . The goal is to identify commercial vendors offering LLM based trainers , today or in the future . This Sources Sought Announcement is issued solely for informational and planning purposes only and is not a solicitation . In your response , please answer the following questions : Company Information and Capabilities : Can you provide relevant experience and past performance with LLM training and development , or extensive experience deploying artificial intelligence / machine learning ( AI / ML ) solutions within a secure enclave , within at least IL5 FedRAMP environment ? Describe your experience with fine - tuning and deploying pre - trained foundation models ( e . g ., Llama , GPT , Claude ) for specific enterprise tasks . If you develop proprietary LLMs , describe the model architecture and the resources required to train it from scratch . Provide specific , quantifiable examples of how your deployed solutions have reduced training time or improved proficiency , preferably with metrics ( e . g ., ' reduced new - hire training from 4 weeks to 5 days '). Please provide specific examples of how your training frameworks have been deployed in other Department of Defense / War ( DoD / DoW ) systems or programs . Please provide examples of past performance that reduced training bottlenecks through on - demand instructional modules . Please provide examples of past - performance containerizing training services for classified enclaves , with full traceability to source documents and configuration - controlled updates . Technical Solutions : Describe your end - to - end process for ingesting technical documents ( e . g ., PDFs , DOCX ), TTPs , and other source materials . How does your solution assist a Subject Matter Expert ( SME ) in validating , refining , and approving the AI - generated training content ? Can you provide on - demand job aids , updated training manuals , and assessment workflows that allow users to update training as the operational system changes . Can you generate and create curricula , learning modules , and as - needed coaching directly from doctrine and task workflows ? Can you demonstrate the ability to deploy virtual instructor technologies that provide real - time guidance and feedback within classified training environments , including IL5 enclaves ? How does your training solution address scalability , interoperability , and integration ? How much data is required for your LLM to considered 80 % trained , to provide effective solutions for training and / or modeling and simulation ? Compliance and Standards : Describe your methodology for ensuring AI - generated content adheres to specific doctrinal standards or regulations that will be provided . How is content traced back to source material ? What specific DoD / DoW security and data handling standards ( e . g ., Defense Information Systems Agency ( DISA ) Security Technical Implementation Guides ( STIGs ), Controlled Unclassified Information ( CUI ) handling ) have you implemented in past projects ? Provide contract numbers or program names as examples . Is there any issue utilizing your LLM solution on a system that is fielded OCONUS ( Outside the Continental United States ) and will be operated by foreign nationals ? Is your organization currently Cybersecurity Maturity Model Certification ( CMMC ) Level 2 certified ? Is your organization currently Cybersecurity Maturity Model Integration ( CMMI ) maturity level 5 for development and services ? Does your solution contain any technology controlled under the International Traffic in Arms Regulations ( ITAR ) or Export Administration Regulations ( EAR )? If so , please describe export control considerations for OCONUS deployment and foreign national access . What is the maximum classification level your solution is currently authorized to support ( Unclassified , CUI , Secret , Top Secret , Special Access Program )? Describe your organization ' s experience with the Authority to Operate ( ATO ) process for classified systems , including any existing ATOs and the authorizing agencies . Innovation and Differentiation : Beyond standard Q & A , what innovative features does your solution offer to accelerate learning and knowledge retention ? ( e . g ., simulation generation , real - time performance feedback , adaptive learning paths ). How does your LLM leverage emerging technologies to enhance performance and capabilities ? What future capabilities are on your development roadmap that could be relevant to our mission of on - demand training ? Cost and Schedule : Can you provide a rough order of magnitude ( ROM ) cost estimate for your proposed solution ? What is your estimated timeline for development , testing , and deployment of the solution ? Identify any existing Government contract vehicles ( General Services Administration ( GSA ) Schedules , Government Wide Acquisition Contracts ( GWACs ), DoD / DoW Enterprise Software Initiative ( ESI ), etc .) under which your solution could be procured . Include contract number ( s ), Special Item Number ( s ), expiration dates , and confirmation of scope applicability . Also describe any current or recent DoD / DoW / Federal contracts where you are performing similar AI / ML training work . What is the typical development lifecycle for similar LLM training solutions from requirements definition through full operational capability ? What are your industry - standard delivery schedules for initial operating capability and full operational capability ? What contract type ( Firm - Fixed - Price , Time - and - Materials , Cost - Plus - Fixed - Fee , hybrid , etc .) is most appropriate for your solution and why ? Please explain your rationale . Risk Management : What are the potential risks associated with your proposed solution , and how do you plan to mitigate them ? Support and Maintenance : How do you ensure long - term sustainability and reliability of your LLM solution ? How stable is the connection to and through your solution ? E . g ., how often would you need downtime for updates and maintenance ? How many support staff members are required to sustain and maintain your solution ? Data Rights and Intellectual Property : What are your policies and approaches regarding data rights and intellectual property for the proposed solution ? How do you ensure that DoD / DoW has the necessary rights to use , modify , and maintain the solution ? Can you provide Government Purpose Rights or Unlimited Rights to the training content generated by your LLM solution ? Please specify which rights apply to generated content versus underlying software / models . What data rights would the Government receive for the underlying LLM models , algorithms , source code , and training datasets ? Are there any restrictions on the Government ' s ability to create derivative works or modifications of the generated training materials ? If so , please describe . What is your policy regarding Government data used to fine - tune or train your LLM models ? Does your company claim any ownership rights to derivative models , weights , or parameters created from Government - provided data ? Describe your approach to ensuring the Government retains full rights to models trained on Government data . Collaboration and Teaming : Are you open to collaborating with other vendors or subcontractors to deliver the solution ? What is your approach to managing partnerships and ensuring seamless integration of components from different sources ? Commercial Terms and ConditionsIs your proposed solution a commercial item as defined in FAR 2 . 101 ? Please explain your rationale and provide supporting documentation if available . What are your standard commercial terms and conditions for similar LLM training solutions ? Please provide a representative sample or describe typical terms . What warranties , if any , are typically offered with your solution ( e . g ., performance warranties , software warranties , up - time guarantees )? What are your standard commercial payment terms and conditions ? Do you offer commercial pricing models ( e . g ., subscription - based , per - user licensing , consumption - based , perpetual license )? Please describe all available pricing structures . SMALL BUSINESS CONSIDERATIONThe pertinent North American Industry Classification System ( NAICS ) codes for this announcement are 541512 and / or 611430 . Any business , regardless of size , in this area of expertise is encouraged to provide a response to this sources sought . Responses from small and small disadvantaged businesses are highly encouraged and the Government encourages teaming / partnering . This requirement involves data that is subject to export control requirements under the Arms Export Control Act ( Department of State ) or the Export Administration Regulations ( Department of Commerce ). Interested parties desiring to do business with the U . S . Space Force ( USSF ) shall be registered in the DoD / DoW Central Contractor Registry with a Commercial and Government Entity ( CAGE ) code . SUBMISSION INSTRUCTIONSResponses to this sources sought must be received via this Microsoft Forms Link https :// forms . osi . apps . mil / r / VDKSExuQdk no later than 30 April 2026 . If an interested party would like to submit sensitive or proprietary materials in addition to the Forms response , they must be coordinated with either the primary or secondary points of contact . If the response includes any proprietary information , data , or trade secrets , please clearly mark each page containing such information with an indicator , such as " Proprietary Information " or " Company Confidential ." The Capability statement should be limited to no more than 15 pages . Submissions exceeding this limit may not be reviewed in their entirety . SSC support contractors are supporting the Government on this effort . As such , information submitted in response to this sources sought may be released to individuals who work SSC support contractors . Please immediately notify the primary point of contact if your company does not consent to the release of proposal information to SSC support contractors personnel .

Rocky Mountain E-Purchasing System

2026-05-06