KARL is Databricks AI Research’s published language-model specialization for grounded enterprise search and knowledge reasoning. The technical report explicitly defines KARL as GLM 4.5 Air post-trained with two iterations of multi-task reinforcement learning, rather than only the surrounding search-agent harness. Synthetic question generation, long-horizon solving, and large-batch off-policy learning train retrieval, cross-document synthesis, and numerical reasoning behaviors. Parallel rollouts and aggregation provide optional test-time scaling. The research model is documented in a public report, but downloadable weights and a named public inference endpoint are not established; platform product access does not prove an identical checkpoint.
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