A.S.Helsingö offers premium doors and handles designed to fit IKEA cabinet frames. They currently sell to 14 countries via their online store and are expanding rapidly both online and offline.
Previously, the customers sent a PDF containing their IKEA order by email to Helsingö. From that PDF, a Helsingö sales rep manually matched the suitable doors for every IKEA order. Time-consuming, prone to errors and unscalable. And most importantly, time away from actually working with customers.
Using Aito, Helsingö took their shopping cart creation to intelligent automation era. Now, whenever a customer uploads a PDF to the Helsingö shopping cart online, their order is automatically matched with Helsingö’s product catalog and suitable products are suggested.
Aito is a predictive database that works through a REST API.
The Aito workflow constitutes from 2 steps: 1. Upload data 2. Make queries
In this example case we have already uploaded the data into Aito and only go through what kind of data we have and what kind of example queries you could do using the data.
The Aito console can be used to drag'n'drop CSV files to Aito.
This is an example implementation and the real implementation can differ from the example.
When your data is in Aito Predictive Database, you are ready to make predictions. Here are a few query examples of what you can do.
You can send the queries using cURL or your favorite REST client and change the values to make different predictions.
You can try this case study yourself by following these steps: 1. Copy one of the queries as cURL 2. Modify the query as you like 3. Send the query and witness the magic
Request your instance in the Aito console and drag'n'drop your CSV file on the instance page. Then you're all set to make your predictions!
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