Introduction

Neuralk AI develops powerful Tabular Foundation Models (TFMs) purpose-built for industry applications, delivering state-of-the-art accuracy on real-world ML tasks across commerce, finance, healthcare and beyond.

Seldon

Seldon is our foundation model designed for tabular prediction tasks (classification and regression). It uses In-Context Learning to make predictions based on examples you provide, without requiring traditional model training or hyperparameter tuning.

Zero Training

No hyperparameter tuning needed. Strong baseline performance out of the box.

Fast Iteration

Explore new datasets quickly. Adapt to changing data without retraining.

Scikit-learn Compatible

Familiar fit/predict interface. Works with pipelines and cross-validation.

Flexible Deployment

Cloud API or on-premise. Same SDK, same interface.

Using the Model

Use Seldon with your API key. The task type (classification or regression) is automatically detected from the target variable.

Pass discrete labels to fit():

from neuralk import Seldon

model = Seldon(api_key="nk_live_xxx")
model.fit(X_train, y_train)  # y_train has discrete labels
predictions = model.predict(X_test)

Pass continuous values to fit():

from neuralk import Seldon

model = Seldon(api_key="nk_live_xxx")
model.fit(X_train, y_train)  # y_train has continuous values
predictions = model.predict(X_test)

Use the host parameter instead of an API key:

from neuralk import Seldon

model = Seldon(host="http://your-server:8000")

→ Learn more about On-Premise Deployment

Getting Started

  1. Install the SDK: pip install neuralk

  2. Get your API key: Run neuralk login

  3. Make predictions: See Quickstart

Learn More