Clairic - Cloudflare’s single-pass model for extracting data from text

Clairic is Cloudflare’s new extraction model that pulls structured answers out of text and images in a single pass, without generating output tokens.

Problem: Many repetitive structured-output jobs, like invoice totals, delivery dates, repair costs and short-term traffic forecasts, get sent to frontier LLMs. That is slower and costlier than it needs to be, and the answers can come back mistyped or hallucinated.

Solution: Clairic takes a request with a state (text, plus up to four optional images) and a map of typed fields. It answers all the fields in one parallel pass and returns each value with a confidence score.

What makes it different: It doesn’t write an answer token by token. It extracts, computes, estimates and forecasts directly, and it returns null when the input doesn’t contain the answer. Estimates come back as a median with an 80% interval, so you can see how sure it is. Per Cloudflare, in a claims pipeline, a Clairic → Clef → GLM-5.3 cascade took 19.3 s against 61.7 s for GLM-5.3 on every step, at $6,032 against $11,740 per million claims.

Key features:

• Field types include text, number, date, time, datetime, duration, list, estimate and forecast

• Extracted text spans with character offsets

• Computed values, such as totals and date differences

• Estimates and forecasts with 80% intervals

• Confidence and null probability on every answer

• Charged for input tokens only

Who it’s for: Developers building document processing, claims, invoicing or forecasting workflows who want fast, cheap structured outputs and can put a larger model behind it for the harder steps.

Cloudflare blog post, the model docs and the live demo.