Capitan: You Won’t Forget to Buy Milk Ever Again

Ask yourself how many times you forgot to buy milk or other groceries on your way back home? If you asked me, the answer would be enough times to cause me a headache, so I looked for solutions such as writing a list on paper (I left it at home most of the time) or asked my wife to message me with a list. The latter worked, but you know every such solution becomes old school when you start using Capitan.

Capitan is a smart shopping app developed by Artur Kiulian and his team that tracks your location and shopping habits to learn more about you and suggest items – via notification sent to iPhone or Apple Watch – you usually buy (and are on your shopping list) when you are near a store.

capitan-iphone

The shopping list is at the core of Capitan: It needs your input to make it work, but it’s very easy, thanks to a nice, user-friendly UI. You can create various lists and add items to it, and I really liked that Capitan eases that process with smart suggestions as you type and automatically categorizes them when you hit return. Of course, you can also delete or categorize any item yourself.

One of the neat features of Capitan is group sharing: If you log in with your Facebook account and allow the app to access your address book, you can share your list with family or friends. For some reason this part isn’t completely flawless, as the list keeps refreshing, sometimes unsuccessfully, but hopefully the developer will address this bug in future updates. I was able to add my friends to the list but couldn’t locate some of the contacts from my address book.

Anyways, if you manage to add a contact to the list, Capitan starts to become really handy: Anyone on the list can add items to the list, and what’s more, they will even receive a notification when you are near the store, so they can make last-minute suggestions as well.

How does Capitan manage to do that? As I mentioned before, Capitan tracks your location in the background and uses multiple public sources (APIs) to find relevant stores around you. At the same time it checks if that type of store is relevant to items on the list. For example, if Capitan locates a grocery store nearby, it checks your shopping list for groceries and sends you a notification. Similarly, it will trigger a notification when you are near a store like Ikea or Home Depot.

capitan-apple-watch

I have to admit, that I like this idea and that the app learns where I pick up my stuff, so it will mostly trigger notifications near the types of stores I usually buy things.

Here is what Capitan’s co-founder and CEO Artur Kiulian tells me about the App and why they built it:

“Although an artificial intelligence team working on a shopping list app might sound like overkill, the idea was born from sheer necessity: bootstrapping a startup while living together in a shared apartment makes it frustratingly hard to collaborate on shopping routines. All it takes is just a bit of customer development, which the founding team did more than their fair share of, to learn that the same issue seems to resonate for a huge demographic throughout the US – nobody, and I mean nobody, likes making extra trips to the store to buy forgotten items.”

“Inside the box the app is a combination of machine learning algorithms, years of experience in applied location-based and predictive analytics along with the crowdsourcing of data. All the heavy computation is done in the cloud so mobile device owners don’t need to worry about extensive battery drain which is the case for most location-based apps,” Kiulian said.

It is worth mentioning that the continuous use of GPS in the background affects battery life. In my tests it wasn’t that bad, though. For example, Capitan today accounted for 9% of battery usage and 3% over the past 6 days. But that may show up differently on your device.

Capitan is available for free for both iOS and Android.

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Written by:
Freelance tech journalist István Fekete covers the latest technology news and trends, such as mobile payments, Apple news and app reviews for multiple publications.
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