SearchInk rebrands as omni:us, aims its hand-writing reading AI at insurance industry

Back in 2016 a startup called SearchInk, launched out of Berlin with the aim of combining machine learning with handwriting recognition. The upshot would be the ability to semantically label handwritten documents. Pretty nifty. It went on to raise €4.2 million in seed funding, but after developing this AI to read hard-written documents, it went in search of a market and business model. Not an easy thing to do. After all, what industry needs hand-written documents read at scale, when so many documents today are born digital in the first place? It turns out there was one after-all: the insurance industry.

In that sector, claims forms, emails and invoices are currently processed manually. But CEO and co-founder Sofie Quidenus-Wahlforss realised that her company’s technology could significantly reduce the time and cost spent on administrative tasks, as well as the risk of human error.

So today, SearchInk rebrands as omni:us, a next generation AI service with two main products aimed squarely at the insurance industry: omni:us Claim and omni:us Policy. The idea is to be able to process digital documents, some of which contain handwriting, by classifying them and extracting the valuable data.

Omni:us is launching these products first in the DACH region, and claims to be working with over half of the top 10 insurance providers. It also says it can deploy its claims management and policy extraction products into an organisation within a matter of weeks. It’s now raise a total of $6.5 million from individual angels and VC, including Anthemis.

Quidenus-Wahlforss said: “Industry predictions show that insurance data will grow by 94% in 2018, 84% of which will be in highly variable documentation. However, in the future, there is also huge potential to apply omni:us technology to many other diverse industries such as finance, manufacturing, transportation and healthcare.”

She added that “We see customers improving their claims turn around time by 80% and all of that at 75% of the original costs. Why is this the case? Fundamentally, because with omni:us manual interventions can be reduced to a minimum, due to the supervised machine learning approach. One of our clients could speed up the comparison by an average 90% at only 80% of the costs.”

Furthermore, the AI could analyze policies with an annual value of only 250 Euro, which normally be a waste of a human being’s time and effort.

Omni:us is now in the process of raising a further funding round this year, opening an office in the US and growing its team.

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