Banking & risk
Credit scoring, fraud detection, and lifetime-value prediction from customer and transaction tables.
Train nothing.Predict anything.
Foundation models for structured data that replace XGBoost with one API call.Free and open source. Try Nori locally on private data — no training, feature engineering, or tuning.
Trusted by leading companies
Why this matters
The world runs on tables.
The predictions that run a business aren't made from prose or pixels. They're made from rows and columns. Tabular data is the most valuable data most companies own, and the hardest to get right.
View industry use cases
Retail & supply chain
Demand forecasting, pricing simulation, inventory planning, and scenario analysis.
Insurance
Claims severity, underwriting risk, and churn — straight from policy and claims tables.
Healthcare
Readmission risk, cost prediction, and triage from structured clinical records.
Infrastructure
Capacity planning, throughput forecasting, incident risk, and predictive maintenance.
Growth & marketing
Conversion, lifetime value, and propensity scoring across the funnel.
The problem
Classical ML repeats the same work for every dataset.
Feature engineeringRebuilt from scratch for every dataset.
Training and tuningWeeks spent searching for the right parameters.
Text and numbersStill trapped in separate models.
Structured data foundation models
Nori replaces the boosting workflow.
It returns predictions without feature engineering, training, or hyperparameter search.
Synthefy foundation model
from synthefy_nori import NoriRegressor
model = NoriRegressor()
predictions = model.predict(X_test, X_train, y_train)
One forward pass
to produce predictions
Beats tuned XGBoost / LightGBM
zero-shot, with no feature engineering, training, or hyperparameter tuning
Managed API served on SOC 2 Type II certified infrastructure — HIPAA, GDPR, and zero data retention
Businesses
For Business Teams
Developers
For Developers
Completely open-source code and weights, or use Nori through the managed API.
