Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
AI Overview
This RFP seeks a schema-driven decision management system with governed AI capabilities to transform complex acquisition trade studies into auditable, human-controlled decision packages. The prototype will demonstrate how agentic AI can process digital engineering data while maintaining traceability, bias detection, and decision readiness assessment.
This summary is AI-generated from the official solicitation.
Key Details
Official Description
This topic will prototype and demonstrate a schema-driven Decision Management (DM) foundation plus a governed agentic AI layer that turns messy decision requests into auditable, signer-ready Decision Packages. The focus is proof by demonstration (not a full product build) to show the approach works for point trade studies and long-horizon acquisition decision programs with traceability, robustness, and human control. AI can process vast amounts of structured and unstructured data from Digital En...
Change History
Informational change · Description + Requirements
Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
The Q&A was restructured and substantively expanded, with the previously pending answers now filled in.
- Phase II open-source wording clarified: The government does not require the full solution to be open source. Offerors may use a commercial licensed product, provided schema, data formats, and APIs are openly published. No minimum list of open elements is mandated beyond one initial government copy.
- Ground-vehicle domain representation: Left to the offeror. No Army ontology or GVSC/PAE model library is required for Phase I.
- Human-AI interaction guidance: No specific Army or DoW document is required for traceability.
- Bias checks: Both cognitive/decision-process bias and statistical model-output bias are in scope. Offerors should propose at least one check of each type with a pass/fail condition.
- Hosting: Offeror-hosted Phase I demonstrations are acceptable using unclassified, non-CUI data in a commercial cloud. Government hosting, including DREN, is deferred to Phase II.
- Demonstration data: Decision cases are classified, so offerors should use synthetic or generic unclassified examples. CPARS data is unavailable. PAE guidance is still pending on a preferred program type.
- Demonstration scope: Both Phase I demonstrations address the same decision question, using notional or open-source acquisition data.
Informational change · Description
Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
Description information changed.
Informational change · Status
Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
Status changed from status: Pre-Release to status: Open.
Informational change · Description
Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
Description information changed.
Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
New opportunity: Agentic-AI, Schema-Driven Decision Management for Auditable Studies and Acquisition Decisions
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