Glossary

Total Information Capture

Every signal that can inform a decision is captured before it becomes dark data - no sampling, no sampling bias.

core concept

Definition

Total Information Capture is the foundational principle of the Sensor layer. Unlike conventional analytics that sample data or process batch summaries, the Sensor captures every signal at the protocol level - multimodal across video, audio, text, and visual semantics. Processing 2.4M+ signals per second continuously, the system ensures no dark data is created. Network connections, exact timestamps, subtle behavioral patterns, and cross-signal relationships are all preserved. This completeness is what enables downstream causal analysis and deterministic execution: you cannot make deterministic decisions from sampled data.

Why It Matters

Complete signal capture is the foundation of informational superiority. If you miss signals, you miss causes. Sentient misses nothing.

Related Terms

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