SBIR/STTR Research Award

Leveraging Time Series Synthetic Data Generation to Predict the Intentions and Actions of Mobile Adversary Hardware and Personnel

Award identifier 3064cc98808a2e05d2fe8a1f6e2954985349e48f1bac31407933a5baefeb1cafAwarding agency Department of Defense · Air Force

Award amount

$74,998

Program and phase

SBIR · Phase I

Award year

2023

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
LEXSET.AI INC
Proposal award date
2023-05-02
Contract end date
2023-08-04
UEI
CJLFZ2FMV7P9
Solicitation number
X23.5
Topic code
AFX235-CSO1

Research abstract

Lexset aims to add new agent-based modeling capabilities to its Seahaven synthetic data software platform to enable the DAF to autonomously predict adversary intentions and actions in multiple warfighting domains. Through this Phase I and its follow-on ef

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

7 SBIR/STTR records share this UEI (2022–2025). Reported award amounts total $5,224,225. Reported amounts are not federal obligations.

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

Agencies: Department of Defense

Agency intelligence

Department of Defense

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