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VerifiedRobotics Engineering· Founded 2024

Analog Physics Inc

Analog Physics Inc. is a deep-tech company developing deterministic, certifiable intelligence for autonomous robotics and agents that must operate safely, independently, and at scale. The company’s work is based on a fundamentally different approach from conventional artificial intelligence. Analog Physics does not use neural networks, training datasets, or statistical prediction. Instead, it engineers intelligence as a physical reasoning system. Mission goals, operating limits, and safety rules are converted into formal logical constraints that define what actions are allowed. When multiple valid actions exist, the system resolves them through physically grounded interference mechanisms rather than probability or optimization. This architecture is deliberately application-agnostic. It produces bounded, auditable decision outputs while leaving physical control, actuation, and system integration to the end user or platform integrator. This separation of reasoning from execution enables certification, accountability, and deployment in safety-critical environments. Analog Physics is also developing a compact, edge-deployable quantum cognitive core designed to operate at room temperature without large infrastructure. A central innovation is treating nuclear decay as a stabilizing mechanism rather than a source of error, allowing reliable quantum reasoning in small, mobile form factors. The technology has been validated on real operational sensor data, including internationally collected counter-drone datasets, demonstrating deterministic behavior, significantly reduced false alarms, and faster decision generation than conventional machine-learning approaches. Analog Physics is guided by a single principle: autonomous systems require engineered intelligence, not trained approximations. Determinism, auditability, physical grounding, and scalability are treated as foundational design requirements.

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HeadquartersUsa, United StatesEmployees10(1 to 10)Founded year2024Websiteqai.aiLinkedIn profileLinkedIn

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