Technology
Technical architecture and implementation details of the DetectX verification system.
What DetectX Builds
DetectX develops forensic verification systems for detecting structural AI signal evidence in media content. The platform is designed to provide deterministic, reproducible analysis that can be independently verified.
Unlike probabilistic detection systems that output confidence scores, DetectX systems report binary structural observations: either AI signal evidence was observed, or it was not. This approach eliminates the ambiguity inherent in percentage-based classifications.
DetectX Audio — Enhanced Mode Architecture
DetectX Audio uses a dual-engine verification system called Enhanced Mode. This architecture combines two complementary engines to maximize human protection while maintaining effective AI detection.
Classifier Engine (Primary): A deep learning classifier trained on over 30,000,000 verified human music samples. This engine serves as the primary filter, optimized for near-zero false positives on human content. If the Classifier Engine determines content is human, the verdict is trusted immediately.
Reconstruction Engine (Secondary): When the Classifier Engine score exceeds the 90% threshold, the Reconstruction Engine activates. This engine separates audio into stem components, reconstructs the signal, and compares the reconstruction differential against known patterns. This secondary analysis boosts AI detection accuracy.
The dual-engine approach ensures human creators are protected (<1% false positive rate) while maintaining strong AI detection for confirmed AI-generated content.
Genre Note: Some genres may exhibit signal characteristics similar to AI-generated music due to heavy processing: Electronic/EDM, Hip-hop (heavily produced), Dance/House, and Lo-fi. These genres may have slightly higher false positive rates. The system prioritizes human artist protection as its primary design constraint.
Core Technical Principles
Deterministic Processing
Every step in the verification pipeline produces identical output for identical input. There are no random seeds, no stochastic sampling, and no model inference variability. The same audio file will always produce the same verdict.
Human-Safe Baseline Construction
Baselines are constructed exclusively from verified human-created content. The system is calibrated to ensure that human creative work does not trigger false positives. Human safety is a design constraint, not an optimization target.
Dual-Engine Verification
The system uses two complementary engines: Classifier Engine (deep learning) for human protection and Reconstruction Engine for AI detection boost. The Classifier Engine is trained on 30,000,000+ verified human samples to ensure <1% false positives.
Binary Verdict Model
DetectX does not output confidence percentages or likelihood ratios. The system reports binary structural observations only: evidence was observed, or evidence was not observed. This eliminates the misinterpretation risks associated with probabilistic outputs.
Verdict Model
The DetectX verdict model is intentionally constrained to two possible outcomes:
Structural signal behavior exceeded what can be explained by human creation alone.
Structural signal behavior falls within human-normalized baseline parameters.
These verdicts describe structural observations only. They do not imply authorship, creative intent, or legal attribution.
System Boundaries
DetectX Audio operates within clearly defined boundaries:
- •Mix-level audio only (no stem separation or source isolation)
- •Minimum duration requirements for reliable analysis
- •Supported formats: WAV, MP3, FLAC, AAC, OGG
- •Maximum file size: 200MB per analysis
- •No real-time streaming analysis
Deployment Contexts
DetectX Audio is designed for integration into professional workflows where forensic verification is required:
- •Content submission pipelines for labels and distributors
- •Pre-release verification for studios and producers
- •Catalog auditing for rights holders
- •Independent verification for creators and artists
The system provides a shared, deterministic reference that all parties can independently verify.