FOR THE MOST AMBITIOUS DATA TEAMS

Train nothing.
Predict anything.

First predictions in seconds, not weeks. Skip task-specific training on your enterprise data.

Start predicting

See what you can do

Used by teams through open source

PREDICTIONS & INSIGHTS

First predictions in seconds.
More use cases per team.

More use cases. Zero training.
Predict demand, revenue, and customer value with one pretrained model. Each data scientist can tackle more tasks without training another model.
Try your first prediction
Add the data your models are missing.
Automatically find relevant external data and merge it with your tables and text to improve predictions.
Explore data enrichment
Turn prediction drivers into business insights.
See which inputs raise or lower predicted customer acquisition, revenue, or demand. Give business teams clear drivers to investigate.
Explore interpretability

USE CASES

Any prediction task. Any structured data. One model.

Use the same pretrained model across your team's prediction tasks. Bring tables, time series, and relational data prepared as model-ready features.

01
Retail
- Dynamic pricing
- Inventory management
- Demand forecasting
02
Finance
- Credit scoring
- Fraud detection
- Risk analysis
03
Networking
- Predictive maintenance
- Dynamic allocation
- Capacity planning
04
Medical
- Readmission risk
- Clinical outcomes
- Early detection
05
Logistics
- ETA prediction
- Fleet routing
- Hub capacity
06
Energy
- Load forecasting
- Outage risk
- Plant reliability
07
Gaming
- Player churn
- Matchmaking
- In-game LTV
08
SaaS
- Churn prediction
- Expansion revenue
- Conversion

Example applications. Validate for your data and use case, with domain-expert review for medical and financial decisions.

Discuss your use case

Start with Python.

Run Nori locally. Fully open-source code and weights on GitHub and Hugging Face.

Python docs GitHub

Hugging Face

Your next predictionPython

$ pip install synthefy-nori

1from synthefy_nori import NoriRegressor
2
3model = NoriRegressor(model="nori-30m")
4model.fit(X_train, y_train)
5predictions = model.predict(X_test)

Open-source code & weightsApache 2.0

Call Nori.
We handle the rest.

Get predictions through a hosted API. No model hosting or GPU infrastructure to manage.

Hosted on Baseten

SOC 2 Type II
HIPAA-eligible
GDPR support

HIPAA requires an eligible deployment and a signed BAA.

API docs Get an API key

Hosted NoriManaged API

$ pip install synthefy

1from synthefy import SynthefyNoriClient
2
3with SynthefyNoriClient(
4    mode="remote", model="nori-30m"
5) as client:
6    predictions = client.predict(
7        X_train, y_train, X_test
8    )