AutoMerit Architecture

Live Ambient Voice Parsing & Zero-Knowledge Evaluation Engine

Replacing bloated manual scoring with real-time NLP voice parsing, isolated cryptographic sandboxes, and automated score unblinding.

Core Components

Engine Specifications

Built for instantaneous execution, zero evaluator bias, and complete participant privacy.

Zero-Knowledge Sandbox

Ambient Voice Parsing

Post-Event Unblinding & Score Packets

Transient bib assignments (e.g., Bib #104) locked in an AES-256-GCM sandbox to eliminate PII exposure and evaluator bias.

Web Speech API and NLP worker parse spoken evaluation rubrics into itemized JSONB deductions in real-time without hardware cameras.

Relational database lookup maps public bibs back to registered athletes, instantly populating tiered itemized score packets on parent dashboards.

Applied Case Study

Real-Time Routine Deduction Flow

Live Stream Telemetry

Evaluators speak directly into ambient microphones using standard scoring lexicon. The worker continuously processes audio streams into structural deductions without requiring manual keypad input.

Spoken Input: "flexed feet 0.1, bent knees 0.2"

Deductions: Flexion (-0.10), Knee Angle (-0.20). Cumulative deductions calculated automatically.

Evaluator voice patterns translate immediately to localized JSONB schemas while identity data remains shielded in the AES-256-GCM memory layer.

9.70

Final Calculated E-Score

Contact Engineering

Deploy Zero-Knowledge Scoring

Integrate AutoMerit's ambient voice engine into your event infrastructure today.