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This funding round highlights growing market demand for tools capable of distinguishing human-authored content from synthetic text generated by frontier large language models. Pangram's new model leverages a "synthetic mirror" training approach, focusing on stylistic patterns rather than just statistical probability to identify AI-assisted writing with high accuracy. The development underscores the critical need for verification infrastructure as generative AI scales across information ecosystems.

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As AI content floods the internet, Pangram raises $9M to detect it

TechCrunchJuly 29, 20266 min read

Pangram has raised $9 million to scale its AI detection software. The startup has also released a new AI text detection model, Pangram 4, and an AI image detection model in research preview.

New York-based AI detection startup Pangram is on a mission to combat the AI slop infestation spreading across the internet, and it just raised $9 million on a bet that demand for tools that distinguish human-generated content from AI-generated text will only grow. Pangram’s fundraise — led by Menlo Ventures, with participation from Haystack, ScOp, Script Capital, and Cadenza — comes as the startup also launches its next-generation AI text detection model, Pangram 4, and an AI image detection model, Pangram Image. Pangram says the new text detection model is over 99% accurate at finding AI-assisted writing and mixed human-AI content, plus it can more easily detect AI humanizer programs. The AI image detector is only available via research…

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