Cloudflare debuts Clairic: A System One extraction model that skips token generation
Cloudflare has launched a preview of Clairic, a new 'System One' extraction model designed to pull typed values with confidence scores from unstructured data in a single forward pass, claiming faster and cheaper performance than traditional LLMs.
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US cloud computing company Cloudflare announced the preview of Clairic on October 19, 2026, defining it as a new class of 'System One extraction models.' The model is designed to extract, compute, estimate, and forecast values directly from unstructured inputs like receipt photos, support emails, or CSV files, rather than generating text word-by-word like Large Language Models (LLMs).
According to Cloudflare's official blog, Clairic operates via a single parallel forward pass without producing output tokens, meaning it charges only for input and typically responds in under a second. It returns typed values (such as numbers, dates, and lists) with character offsets and confidence scores, returning null if an answer cannot be found. This design avoids common LLM failure modes like invalid JSON formatting and hallucinations, although the model can still make mistakes.
The concept follows TypeSafe's release of Jev a month prior, which introduced decision models based on Daniel Kahneman's 'System 1' thinking from Thinking, Fast and Slow. Cloudflare states that Clairic is the first model in this new extraction category, specifically targeting tasks that require concrete numerical answers rather than choices or free-form text. Clairic is currently hosted on Workers AI, with plans to release open weights soon.