KNOWLEDGE BASED SYSTEMS INC — Department of Defense STTR Phase II: MDA19-T003

KNOWLEDGE BASED SYSTEMS INC — STTR Phase II award from Department of Defense.

Phase II STTR prototype / development signal

  • Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
  • Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
  • Obligated amount $1,407,796 is consistent with substantial Phase II-scale effort; compare to related awards from the same agency.
  • Topic code MDA19-T003 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.

Informational capture context from public federal data — not legal or bid advice.

Amount
$1,407,796
Agency
Department of Defense · Missile Defense Agency
Program / Phase
STTR · Phase II
Topic
MDA19-T003
Solicitation
19.C
NAICS
Place of performance
TX
Period
2021-05-27 → 2023-05-26

Description

Knowledge Based Systems, Inc. (KBSI) proposes to design, demonstrate, validate, and harden an innovative solution for the analysis and enhanced understanding of federated simulation output data in a manner that consistently increases data analysts’ efficiency and effectiveness. Building off the successful Phase I ‘Data Retrieval Assistant for COnsistent simulation data exploration using semantic NL interfaces (DRACO)’ solution, the proposed Phase II project will design, prototype, validate, and harden the DRACO innovation, leading to accelerated technology transition and commercialization. The flexible DRACO architecture design will allow for affordable integration and rapid transition to a Modeling and Simulation (M&S) ecosystem. Innovations include (i) semantic disambiguation methods for processing Natural Language text inputs, (ii) hybrid Artificial Intelligence (AI) methods for automated query generation, (iii) dynamic and interactive human machine interfaces for enhanced data understanding, and (iv) automated learning methods to enable dynamic adaptation of the search and exploration over extended time. Approved for Public Release |21-MDA-10789 (21 Apr 21)