Goodfire AI Review 2026

Mechanistic interpretability platform — Silico — that lets teams understand, debug, and steer neural networks with the precision of written software.

Goodfire is a mechanistic interpretability company building tools to look inside neural networks the way developers look inside code. Their flagship platform, Silico, exposes the latent features and circuits inside a model so teams can debug failure modes, remove unwanted behaviours, and steer outputs at a much finer grain than prompt engineering. The pitch is to move AI development 'from alchemy to precision engineering': instead of fine-tuning on more data and hoping the model behaves, you can find the specific features responsible for a hallucination, refusal, or bias and edit them directly. Goodfire has worked with frontier labs and is positioning Silico as a platform for AI safety researchers, model-developing companies, and regulated industries that need defensible explanations of model behaviour. Access today is request-based rather than self-serve, with pricing negotiated per engagement. Best for AI research teams, safety-focused engineering groups, and enterprises building proprietary models who need interpretability tooling beyond log probabilities and attention heatmaps.