Strucai's APIs

Greetings ! Try out our GeoStarbucksRanking API by inserting your Danish street name to find most connected Starbucks based on stops nearby

Street Name :

OR try out our StopsNearby API by inserting your street name to find closest public transport stops

Street Name :

Compare with our unranked GeoStarbucks API by inserting your street name to find closest Starbucks

Street Name :

What is GeoStarbucksRanking API about?

This is a Proof of Concept (PoC) of a Strucai API with a goal to enrich processes using combined chained API requests. GeoStarbucksRanking API combines GeoStarbucks API with StopsNearby API by toplisting Starbucks with highest count of public transport stops nearby in range of 300m. GeoStarbucksRanking API is an example of an enriched chained API request where users get a better experience.

Strucai makes APIs similar to the one above and combines connected elements with machine learning enrichment. An example could be that the above result consist of 10 different Starbucks addresses. A way to decide which one to visit could be based on a model. This model should then make a better prediction on for instance whether the place will be too busy or totally empty. If a model is trained on customer data showing number of payments (approx no. of clients) during open hours for a whole year, then in combination with an estimate of local neighbourhood popularity it may be able to predict next years no. of clients on a given day. Another parameter based on data about safety or public transport connections in the area could also be included into the model and form the final choice of which one to visit.