About
Overview
Sulie is a fully managed platform for time series forecasting, powered by the Mimosa foundation model—a transformer-based model specifically designed to outperform traditional supervised approaches in time series forecasting.
Key Features
Sulie provides a robust, production-ready solution for data teams, simplifying time series forecasting at scale. Our foundation model offers accurate, out-of-the-box predictions with zero-shot inference, eliminating the need for pre-existing training data. Whether you’re experimenting in a notebook or scaling to production, Sulie abstracts away MLOps complexity, allowing you to focus on actionable insights from your forecasts.- Zero-Shot Forecasting: Obtain precise forecasts instantly with our foundation model, without requiring training or preprocessing of historical data.
- Auto Fine-Tuning: Enhance model performance with a single API call. We manage the entire training pipeline, providing transparency into model selection and metrics.
- Covariates Support (Enterprise): Conduct multivariate forecasting by incorporating dynamic and static covariates with no feature engineering needed.
- Managed Infrastructure: Focus on forecasting as we manage all aspects of deployment, scaling, and maintenance seamlessly.
- Centralized Datasets: Push time series data continuously through our Python SDK, creating a centralized, versioned repository accessible across your organization.
Getting Started
- Generate an API key from our dashboard.
- Integrate Sulie’s Python SDK into your workflow.
- Follow our SDK Documentation for a complete guide on implementation.
Setting up
Getting Started
Step-by-step guide to get you from zero to forecasting in minutes!
Installation
Guide for installing the Python SDK, essential for forecasting and model tuning.