DON26BZ01-NV010ActiveSBIR

E-2D Large Language Model Entity (ELLMENT)

Department of DefenseNAVY

AI Overview

SBIR seeks development of a domain-specific large language model to help military personnel rapidly extract insights from high-volume operational documents, communications, and tactical data. The standalone AI/NLP system must operate securely with full source attribution and traceability for classified environments.

This summary is AI-generated from the official solicitation.

Key Details

Agency
Department of Defense
Funding Amount
Release Date
March 2, 2026
Due Date
June 3, 2026

Official Description

Artificial Intelligence/Machine Learning (AI/ML) technologies are transforming how complex data is understood and acted upon in operational environments. This SBIR topic seeks to explore the development of a domain-specific LLM system to support rapid insight generation from structured and unstructured documents (e.g., Tactics, Techniques, and Procedures [TTPs]), mission logs, communications, and other high-volume data sources relevant to tactical operations.

The goal is to deliver a modular, s...

Change History

Q&A UpdatedMay 26, 2026 at 5:03 PM

E-2D Large Language Model Entity (ELLMENT)

**Summary of Q&A Changes:** Q11 received a major clarification. The updated answer explicitly permits Phase I to include early LLM experimentation and development, not just architecture/feasibility planning. The Government now accepts either a functioning baseline LLM capability with preliminary evaluation OR an architecture/roadmap approach—both are acceptable. However, Phase II's language implies an LLM should be developed in Phase I; if not, performers must justify why. This significantly expands Phase I scope compared to the initial feasibility-study framing.

Q&A UpdatedMay 22, 2026 at 7:03 PM

E-2D Large Language Model Entity (ELLMENT)

**Q&A Changes Summary:** **New Answers Added:** - **Q1:** Government has no format preference for traceability artifacts, only requires transparency and explainability. - **Q2:** Phase I evaluation criteria weighted equally; priority may shift in Phase II post-testing. - **Q3:** No classified data in Phase I; treating data as unclassified acceptable; abstention testing endorsed. - **Q4:** Proposed evaluation methodology acceptable (no specific composition requirements mandated). - **Q5:** CLI/API prototype sufficient for Phase I; no operator-facing mockup required. **Key Changes:** Questions 1-5 received substantive answers (previously pending). Answers clarify that performers have flexibility in artifact formats, evaluation approaches, and prototype interfaces. Q3 addresses security posture for Phase I unclassified work.

Q&A UpdatedMay 19, 2026 at 8:44 PM

E-2D Large Language Model Entity (ELLMENT)

# Q&A Changes Summary **New Questions Added (5):** - Q1: Preferred artifact formats for traceability/provenance mechanisms - Q2: Weighting of Phase I evaluation criteria (accuracy, relevance, context, bias, trustworthiness, SME evaluation) - Q3: Hallucination/abstention testing with adversarial prompts in Phase I - Q4: Specific evaluation-set composition and SME gold-answer methodology - Q5: CLI/API prototype vs. operator-facing UI mockup requirements **Clarified Existing Answers:** - Q6 (Navy Linguistic Patterns): Public/available data acceptable for fine-tuning - Q7 (NFO Roles): Either single or all specified NFO roles sufficient for Phase I - Q8 (Multi-modal Data): None specifically identified at this time - Q9 (Government Data): Surrogate/proxy/public datasets confirmed acceptable - Q10 (Fine-tuning Requirement): Fine-tuning NOT required; corpus prep + prompt engineering + model selection sufficient - Q11 (Phase I/II Boundary): Clarifies Phase I as feasibility/architecture study, Phase II for working prototype + OITL evaluation **No Changes:** Q12–Q14 (CMMC, template discrepancies, ITAR registration) remain identical to previous guidance.

Q&A UpdatedMay 15, 2026 at 7:38 PM

E-2D Large Language Model Entity (ELLMENT)

# Q&A Summary of Changes **New Questions Added (5):** - Q1: Navy-specific linguistic patterns for fine-tuning examples - Q2: Targeted NFO roles (Air Battle Managers, Weapons Director, etc.) to address - Q3: Specific multi-modal data types identified for architecture planning - Q4: Government-furnished datasets availability; surrogate/proxy datasets acceptable for Phase I - Q5: Clarification on "training" scope—fine-tuning vs. prompt engineering/RAG/corpus prep - Q6: Phase I vs. Phase II boundary—functioning baseline capability vs. architecture/roadmap **Key Clarifications:** - **Government Data:** No operational datasets guaranteed Phase I; offerors may use surrogate, proxy, or publicly available datasets to demonstrate feasibility - **Model Fine-Tuning:** Phase I "training" can be satisfied through corpus preparation, prompt engineering, and RAG—weight modification not required - **Phase I Scope:** Intended as feasibility/concept study focusing on architecture, data strategy, and evaluation framework; working prototype/OITL evaluation deferred to Phase II

Q&A UpdatedMay 14, 2026 at 6:48 PM

E-2D Large Language Model Entity (ELLMENT)

**Summary of Q&A Changes:** One new question added: Q1 clarifies that CMMC Level 2 (Self) certification is required at Phase I contract award (not deferred to Phase II). All other Q&As (Q2-Q8) remain unchanged from previous version.

Q&A UpdatedMay 12, 2026 at 4:54 PM

E-2D Large Language Model Entity (ELLMENT)

**Q&A Changes Summary:** One new question added (Q1) addressing critical proposal submission compliance: Navy's DON Proposal Submission Instructions take precedence over DOW BAA instructions for Technical Volume requirements. Offerors must use the Phase I Conventional Topics technical proposal template from navysbir.com, resolving discrepancies between 12-item BAA requirements and 8-item DON template. All other Q&As (Q2-Q8) remain unchanged from previous version.

Q&A UpdatedMay 11, 2026 at 6:49 PM

E-2D Large Language Model Entity (ELLMENT)

**Changes to Q&A:** Added 1 new Q&A on ITAR compliance (22 CFR 120-130): DDTC registration not required at proposal submission; deferred to Phase II award stage pending classified work requirements.

Status ChangedMay 6, 2026 at 1:47 PM

E-2D Large Language Model Entity (ELLMENT)

Status changed from Pre-Release to Open

Q&A UpdatedMay 4, 2026 at 9:31 PM

E-2D Large Language Model Entity (ELLMENT)

# Q&A Changes Summary **Key Update to Q1 (Previously Unanswered):** - Added clarification that quantum-accelerated processing is acceptable if it prioritizes Phase I constraints - Emphasized system must operate stand-alone with traceability, source attribution, and model transparency - Confirmed broad scenario demonstration preferred (TTPs, mission logs, comms) - Clarified no specific architectural preference (RAG/SLMs acceptable if achieving traceability/explainability) **Q2-Q10:** No changes from previous version. **Net Change:** One substantially expanded answer (Q1) providing technical guidance on quantum computing applicability, architectural flexibility, and emphasis on explainability across diverse mission scenarios.

Q&A UpdatedMay 4, 2026 at 2:54 PM

E-2D Large Language Model Entity (ELLMENT)

**Summary of Q&A Changes:** Added 1 new Q&A (Q1) with 3 sub-questions addressing: (1) specific SWaP benchmarks and quantum-accelerated processing for Phase II, (2) Phase I fidelity priorities (model reasoning vs. physics-based simulation integration), and (3) mission scenario scope (broad vs. deep focus). Navy response deferred hardware specifics to Phase I effort and did not endorse particular architectures (RAG/SLMs). Renumbered remaining questions Q2–Q10 accordingly. No substantive changes to prior answers.

Q&A UpdatedApr 29, 2026 at 7:39 PM

E-2D Large Language Model Entity (ELLMENT)

# Q&A Changes Summary **New/Updated Answers (6 of 9 questions):** - **Q1:** Clarified LLM is net-new, stand-alone capability; future integration anticipated but not Phase I scope - **Q2:** SME engagement possible during Phase I with Navy civilian representatives (TPOCs, PMA-231); more collaboration in later phases - **Q3:** Phase I focuses on text-based NLP only; multi-modal extensibility planning acceptable but implementation deferred to Phase II - **Q4:** No open-source preference; requires U.S.-owned/operated solution with no foreign influence and classified-environment compliance - **Q5:** Hardware/compute constraints (SWaP) to be defined during Phase I; no exact limits specified currently - **Q6:** Unclassified surrogate data and publicly available Navy doctrinal references acceptable for initial development **No changes:** Q7, Q8, Q9 (data provision, award count, Navy data provision remain unchanged)

Q&A UpdatedApr 28, 2026 at 7:40 PM

E-2D Large Language Model Entity (ELLMENT)

Added 6 new Q&As covering: integration with existing E-2D tools, SME feedback availability, multi-modal architecture scope, LLM architecture preferences (open-source vs. commercial), hardware/compute constraints, and government-provided vs. surrogate data. Original 3 Q&As retained with identical answers.

Q&A UpdatedApr 24, 2026 at 7:26 PM

E-2D Large Language Model Entity (ELLMENT)

Q1 and Q3 received new answers. Key clarifications: Phase I focuses on defining architecture and understanding data needs rather than actual LLM training. Example/proxy data acceptable; Navy will not provide training data during Phase I.

Q&A UpdatedApr 20, 2026 at 4:38 PM

E-2D Large Language Model Entity (ELLMENT)

Q&A section updated

Date ChangedApr 14, 2026 at 3:03 AM

E-2D Large Language Model Entity (ELLMENT)

Close Date changed from 2026-04-22 to 2026-06-03

Date ChangedApr 14, 2026 at 3:03 AM

E-2D Large Language Model Entity (ELLMENT)

Open Date changed from 2026-03-25 to 2026-05-06

Status ChangedApr 14, 2026 at 3:03 AM

E-2D Large Language Model Entity (ELLMENT)

Status changed from Removed to Pre-Release

Opportunity RemovedMar 3, 2026 at 4:25 PM

E-2D Large Language Model Entity (ELLMENT)

Opportunity DON26BZ01-NV010 no longer available

Opportunity AddedMar 2, 2026 at 11:14 PM

E-2D Large Language Model Entity (ELLMENT)

New opportunity: E-2D Large Language Model Entity (ELLMENT)

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