Compositional Learning-And-Reasoning for AI Complex Systems Engineering (CLARA) is a grant from Defense Advanced Research Projects Agency (DARPA) that funds fundamental research to develop high-assurance artificial intelligence by tightly integrating automated reasoning (AR) and machine learning (ML) components.

Unlike the dominant industry approach of adding specialized AR systems onto large language models, CLARA seeks to create hierarchical, fine-grained, and highly transparent compositions of Bayesian methods, neural networks, and logic programs. The program aims to deliver verifiability based on AR proofs with strong logical explainability and computational tractability, scalable even to complex systems of systems.

Defense application areas include kill web, supply chain and logistics, wargaming, autonomous systems, command and control, and medical, financial, and legal domains. An information session was held in April 2026.

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