Amazon runs hundreds of millions of forecasts every day to move packages.

Uber makes pricing decisions every few minutes across millions of rides.

Banks score billions of card transactions every day for fraud.

All of this runs on structured data, not language. That's the step change we set out to bring with Synthefy.

Today, we're releasing Synthefy Nori, our first tabular foundation model.

For over a decade, structured data prediction meant the same grind: train an XGBoost or LightGBM model, tune it, ship it, watch it drift, retrain.

Synthefy Nori ends it. Pass your labeled rows as context, get predictions back in seconds. No training. No tuning.

Synthefy Nori Highlights:

> #1 on aggregate across 96 datasets, ahead of TabPFN-3

> Beats tuned XGBoost & LightGBM on ~80% benchmark datasets, with zero training or tuning

> 6M params, ~1/10 the size of its peers

> Fully open source

See next tweet for white paper, Github, Hugging Face