SBIR/STTR Research Award

AI-Enhanced Document Extraction & Analysis for Security Forces Intelligence, Mission Readiness, Base Defense, & Training

Award identifier 551f1a31d7b0d1af0ffed303d54d03e9b6d0c3aa7d3f1775cdef6a31983c3f20Awarding agency Department of Defense · Air Force

Award amount

$1,244,160

Program and phase

SBIR · Phase II

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
KILSAR, INC.
Proposal award date
2025-09-24
Contract end date
2027-06-24
UEI
JYJGRNH19KU4
Solicitation number
X24.7
Topic code
AFX247-PCSO1

Research abstract

Kilsar’s Phase II effort will deliver an AI-powered Threat Intelligence and Decision Support Platform that enables Department of the Air Force Security Forces to access and apply critical threat protocols, SOPs, and legal guidance in real time. The platform supports both connected and disconnected operations and integrates with existing systems, including TAK, BDOC, and Air Force enterprise IT. By leveraging natural-language processing, optical character recognition, and semantic search, it converts large volumes of unstructured documents—TTPs, DOJ protocols, ROEs, and installation SOPs—into a searchable knowledge base accessible via plain-English queries in under five seconds. A human-in-the-loop validation layer lets subject-matter experts confirm and refine AI outputs for legal compliance and tactical accuracy, continuously improving the models.The primary objective of Phase II is to validate performance, scalability, and operational fit at multiple installations. In Months 0–6, Kilsar will refine Kubernetes microservices for OCR, embedding generation, and semantic indexing, then deploy a prototype on TAK tablets at Nellis AFB to measure retrieval latency, classification accuracy, and operator workload reduction. In Months 6–12, field exercises at RAF Mildenhall and RAF Lakenheath will demonstrate offline capabilities and BDOC integration under expeditionary and contested conditions, confirming ? 90 percent accuracy and < 7 s per query while disconnected. Human-in-the-loop sessions in Months 8–14 will capture edge-case annotations to improve model precision over 93 percent. Months 12–18 focus on security accreditation—RMF Step 4, vulnerability scans, and CUI compliance—culminating in a formal Authority to Operate. Pilot demonstrations in Months 16–20 will validate system readiness, operator training, and deployment workflows. Phase II concludes in Month 21 with a technical report and Phase III transition plan.This platform addresses Air Force imperatives for “Digital Advantage at the Tactical Edge” and “Agile Combat Employment” by enabling Security Forces to reduce incident response times by up to 60 percent, cut post-incident reporting time by 50 percent, and lower compliance errors by 25–35 percent. Capturing tribal knowledge via AI-assisted annotations prevents institutional loss and supports rapid, informed decisions under stress. By fielding a scalable, mobile-ready solution that bridges complex threat doctrine with real-time guidance, Kilsar paves the way for enterprise-wide adoption across Security Forces, BDOC units, and allied security organizations, enhancing base defense and force protection in garrison and expeditionary settings.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

8 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $5,540,006. Reported amounts are not federal obligations.

Phases: Phase I, Phase II – Direct to Phase II, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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