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Include your own forecasting models in your app in a couple of minutes.

Let Nixtla's API do all the heavy lifting. No servers to manage, no configuration, no headaches. It just works.

1. 🔑 Get your Token

Click here to authenticate yourself and get a token. You should see the following screen.

2. 👩‍💻 Upload your data

Upload your time series data to a cloud provider and get the url associated. Your data must have the following format. The unique_id column identifies each time series, ds identifies the date (or timestamp) of each observation, and finally y contains the target variable you want to forecast for each time series.

3. 🤖 Choose your model

We have a large collection of models you can use to fit on your data.

🧠 Deep Learning

Univariate

• nhits(Nixtla)
• nbeats (ElementAI)
• nbeatsx(Nixtla)
• tft (Google)
• deep_ar (AWS)
• lstm(Schmidhuber)
• esrnn(Smyl)
• DeepAR(Amazon)

Multivariate

• Transformer Models (Google)
• DeepVar (Comming Soon)

Statistical Models

• arima: AutoARIMA Model
• seasonal_exponential_smoothing
• prophet(Facebook)
• complex_es
• ets (Top 5 in M3)`

4. 🚀 Train your model in your fav language.

Make a REST call. In the following example, we use Node, but you can use the programming language of your choice.

5. 🔮 Forecasts with your trained model

Once the model is fitted, you can start to produce forecasts using a REST call in two simple steps. Just follow the following instructions.