Updated March 27, 2026
Guide Labs is building the first inherently interpretable LLMs. Their open-source Steerling-8B model features a novel concept layer inserted into the transformer architecture that makes every generated token traceable back to its training data. Unlike post-hoc explainability tools, Guide Labs bakes interpretability directly into the model, achieving 90% of standard model capability with less training data. YC-backed with $9M seed.
Turns everyday words and actions into usable training data — converting natural-language interactions into structured datasets for model training.
Core capabilities each platform advertises.
What each tool does well, and the limitations to keep in mind.
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