Today, we're announcing a preview of a new class of System One-style models: extraction models. Our first one, Clairic, is available hosted on Workers AI as @cf/cloudflare/clairic.We intend to release the model open-weights soon. Clairic is an extraction model that is able to extract, compute, estimate, and forecast values from unstructured inputs — all at a significantly higher accuracy, faster latency, and cheaper cost than traditional LLMs.
When System One models were announced by TypeSafe a month ago, it took the industry by storm. As referenced by TypeSafe in their blog and defined by Daniel Kahneman’s book Thinking, Fast and Slow, a System One model should be fast and precise, which contrasts a System Two model that is capable of deliberate reasoning (like LLMs). With this, TypeSafe introduced Jev — a model that is purpose-fit for a specific use case, and priced accessibly given its niche domain. It excelled where LLMs failed, helping users make decisions based on probabilities and well-typed outputs. The introduction of Jev prompted people to start thinking about a new class of models that were not LLMs and how to integrate them into their workflows.
