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"Compositional Learning-And-Reasoning for AI Complex Systems Engineering (CLARA)" is currently closed and not accepting applications.
Compositional Learning-And-Reasoning for AI Complex Systems Engineering (CLARA) is a fundamental research program from DARPA's Defense Sciences Office that funds development of high-assurance AI systems by tightly integrating automated reasoning (AR) and machine learning (ML) components.
Rather than bolting AR onto large language models, CLARA aims to create a hierarchical, fine-grained, and verifiable composition of Bayesian methods, neural networks, and logic programs that provides both ML speed and AR-based logical explainability. Target application domains include autonomous systems, command and control, supply chain and logistics, kill webs, wargaming, medical, financial, and legal systems.
Total award value is up to $2,000,000 across a combined Phase 1 base and Phase 2 option. The application deadline was April 10, 2026.
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CLARA: Compositional Learning-And-Reasoning for AI Complex Systems Engineering | DARPA Department of War organization.
CLARA: Compositional Learning-And-Reasoning For AI Complex Systems Engineering CLARA: Compositional Learning-And-Reasoning for AI Complex Systems Engineering Today, the dominant industry approach to artificial intelligence (AI) is to tack specialized automated reasoning (AR) components onto a large language model (LLM) or other similar machine learning (ML) system.
These ML-centric systems typically have weak assurance; the “tack-on” approach is an importantly limited way of providing assurance or safeguards. The Compositional Learning-And-Reasoning for AI Complex Systems Engineering (CLARA) fundamental research program is designed to tightly integrate AR and ML components to create high-assurance AI — which is expected to scale even to complex systems of systems.
Integrating the two different branches of AI will provide the speed and flexibility of ML with verifiability based on AR proofs that have strong logical explainability and computational tractability. In more detail, CLARA is anticipated to create powerful methods for the hierarchical, fine-grained, highly transparent composition of important kinds of ML and AR components, including Bayesian, neural nets, and logic programs.
CLARA aims to create a theory-driven algorithmic, highly reusable, scalable foundation for high assurance plus broad applicability, useful for many crucial defense and commercial realms which may include, but is not limited to: Kill web, supply chain & logistics, and wargaming Autonomous and command & control Medical, financial, and legal Information session presentation
According to the current listing, eligibility includes: Universities, research organizations, and small businesses. Confirm the full requirements in the official notice before applying.
The current listing shows up to $2,000,000 (total award value for combined Phase 1 base and Phase 2 option). Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was April 10, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Compositional Learning-And-Reasoning for AI Complex Systems Engineering (CLARA) is funded by Defense Advanced Research Projects Agency (DARPA), Defense Sciences Office (DSO). Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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