Internal state
Observing understanding
Read the signals a system reveals as it operates — confidence, drift, and the gap between prediction and reality.
Pelagic Platforms builds the instruments to observe, evaluate, and certify the internal state of physical AI systems as they act in the world.
Read the signals a system reveals as it operates — confidence, drift, and the gap between prediction and reality.
Procedural environments matched to real conditions surface the slow failures that snapshot tests miss.
Whether a system that has adapted itself remains able to absorb feedback — the question behind agentic safety.
Structured, auditable evidence for evaluating, certifying, and pricing the risk of autonomous systems.
A complete stack for observing, evaluating, and certifying the internal state of embodied AI.
Real-time observation of internal state as systems operate in dynamic environments.
Procedural environments matched to real operating conditions for long-horizon testing.
Structured evidence becomes the basis for certification and risk assessment.
Autonomous robots in unstructured environments where perception and action must stay aligned.
Self-driving systems where understanding drift can have serious consequences.
Continuous operation that depends on accurate, maintained world models.
Shared instrumentation for studying how learning systems hold and revise understanding.