How Parsifer Works

The Parsifer platform uses a four-step process to determine whether an AI system is using specific source content:

1.    Semantic Fingerprinting – the process starts by analyzing a sample of your work to generate a semantic fingerprint of its characteristics: your unique DNA as a creator. This fingerprint (FP#1) features metadata that represent source content.

2.    Prompt Generation – next, we use FP #1 to generate an automated prompt that queries one or more AI systems. Think of this process as the digital equivalent of dusting a crime scene for fingerprints.

3.    LLM Response – once an AI system produces output based on our prompt, Parsifer then generates a second semantic fingerprint for the AI system output (FP#2).

4.    Fingerprint Matching – this is where FP# 1 and FP#2 are compared, yielding a probability assessment that your content has been used by the AI system.

Why Parsifer is a Gamechanger

There’s a lot of hype about AI. You might even be under the impression that there are solutions out there to protect your content. Solutions like watermarking, bot trackers, stylometry and firewall security are useful but they dance around the edges of the deeper problem – the extremely difficult technical challenge – of identifying the content used to train an AI model after that content has been sliced, diced and regurgitated by the AI. No one else is doing that – except Parsifer.

Register now for our Pilot Program if you want to know the real truth about how your content is being exploited.