extraction-models
Latest stories covering extraction-models, with summaries and links to related coverage.
1 stories · 1 reports · page 1 of 1
Connected topics
Introducing Clairic, a new System One class of extraction models
tool
21 min read
Cloudflare has released Clairic in preview on Workers AI as @cf/cloudflare/clairic, introducing a System One extraction model designed to return typed values from unstructured text and up to four images. The company plans to release open weights later. Clairic can extract source spans, names, dates, numbers and lists; compute values such as totals or date differences; estimate bounded values with medians and 80% intervals; and forecast time-series values. It processes requests in a single forward pass without generating output tokens, returning typed values or null along with confidence scores and, for scalar fields, a probability that the value is absent. Cloudflare says Clairic is intended for tasks where generative LLM output requires parsing and validation, including invoice processing, receipt reading and support-ticket triage. In a 21-day test forecasting daily TSA checkpoint volumes, Cloudflare reported a 3.3% average error and said 17 of 21 actual counts fell within Clairic’s 80% prediction intervals. A damage-claim workflow combining Clairic, Cloudflare’s Clef decision model and GLM-5.3 took 19.3 seconds and cost $6,032 per million claims, compared with 61.7 seconds and $11,740 for an all-GLM-5.3 workflow, according to Cloudflare. The company cautions that longer arithmetic chains, unfamiliar estimates and detailed long-horizon forecasts remain limitations.