Cloudflare Previews Clairic, 49% Cheaper on Claims Pipeline

19.3 seconds versus 61.7 seconds. That is Cloudflare's headline comparison in a preview announcement for Clairic, a new extraction model it is launching on Workers AI as `@cf/cloudflare/clairic`.

"Clairic is an extraction model that is able to extract, compute, estimate, and forecast values from unstructured inputs," the Cloudflare post by Michelle Chen reads. The framing is that extraction belongs to a different class of model than conversational LLMs. "A System One model should be fast and precise, which contrasts a System Two model that is capable of deliberate reasoning."

The showcase is a damaged-product insurance claim pipeline. Clairic pulls typed values out of the customer email, hands them to Clef, a decision model, for approval, and then an LLM writes the customer response. Against an all-LLM baseline, Cloudflare says "the cascade finished in 19.3 seconds against 61.7 seconds: 69% less time, or about 3.2 times faster." Cost per million claims comes to $6,032 against $11,740.

On forecasting, Cloudflare ran Clairic on 21 days of TSA passenger counts. "Across the 21 days, Clairic's forecasts were off by 3.3% on average, and 17 of the 21 actual counts landed inside its 80% interval."

Cloudflare is upfront that the model is early. "Reading is strong, but multi-step arithmetic isn't yet," the post says. Forecasting is "basic." The baseline LLM in the comparison is not named. "We intend to release the model with open weights soon," Chen writes.