Anyone who has ever tried to read the identification number on their car tires in a dimly lit garage knows the problem: black writing on a black background. The door is wide open for errors, but in some markets, like the US, it’s mandatory to register new tires when they are put on. And one doesn’t want to imagine the problems which could be caused by manual and error-prone process of checking of passport numbers or serial numbers of weapons. For Anyline, it doesn’t matter whether it’s a winning number code printed under the bottle cap, reading the meters for electricity, gas or water, the license plate of a wrongly parked car or even the number on the ear tag of Finnish reindeer!
Anyline teaches smartphones how to read. QR codes and barcodes are becoming unnecessary, as smart phones can now extract and interpret information recorded via their built-in camera. The Anyline toolkit simply scans, reads and processes everything – without the need for an internet connection – and it can be easily integrated into apps or websites.
At the end of 2014, Anyline built its first prototype and discovered how incredibly challenging it was to develop Optical Character Recognition (OCR) on a mobile phone – the only device platform which is cheap, portable and widely available enough for a large-scale application in industrial and enterprise use cases. Two years later, Anyline’s first scanning solutions were ready for the market and best of all, are easy to download and integrate with a rapid time to market for their customers. After some classic start-up teething problems, things have really taken off for Anyline since 2017!
Senovo invested shortly after in 2018 and also participated in a series-A financing round one year later. With a compelling email, Anyline co-founder and CEO Lukas Kinigadner made a big impression on Senovo’s Frederick von Mallinckrodt. After a few conversations, Frederick was certain: „Lukas has the right founder’s DNA, is down to earth, – and very importantly has a really good vision on how mobile devices can be used to solve a massive number of manual business processes.“
This additional investment allowed Anyline to make a big move into the US market with a Boston-based office – which brings us back to tires: Like every other use case, the automated reading of the Tire Identification Number (TIN) has an incredible value, which Anyline can calculate to the cent, according to Lukas: „Doing it manually, reading and entering the TIN numbers of a tire set takes four minutes – Anyline accomplishes the very same job within ten seconds.”
And the story doesn’t stop with the current status quo on tires and serial numbers: computer vision and AI-based machine learning on top of currently 200 million data sets are making Anyline increasingly smart. The next features – surface or signature recognition – are already in the pipeline.
This is why it doesn’t come as a surprise that Lukas simply laughs when you ask him about scaling: One German automobile manufacturer alone (which is already an Anyline customer) estimates that within the company there are currently around 600 unsolved OCR cases that are still being treated manually…