WhatAn API and scoring engine that detects AI-generated content by pattern-matching against a continuously updated corpus of LLM writing tropes, going beyond simple perplexity scores to identify specific stylistic fingerprints.
SignalThe existence and viral popularity of a curated tropes list shows that humans can reliably spot AI writing through specific, enumerable patterns — but no one has turned this into a systematic, productized detection layer that platforms can integrate.
Why NowAI-generated content has flooded every platform in the last 18 months, and existing detectors (GPTZero, Originality.ai) have high false-positive rates because they rely on statistical methods rather than pattern-based trope detection.
MarketContent platforms, publishers, academic institutions, and hiring platforms pay; TAM $2B+ in content integrity. Competitors like GPTZero and Originality.ai miss the pattern-based approach and have trust/accuracy problems.
MoatContinuously updated trope database that improves with each new model release, creating a data flywheel as models evolve — detection patterns need constant human curation which is hard to replicate at scale.
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