(Interview with CEO and Founder Ciro Greco)
(1) Describe your startup.
Tooso is a knowledge graph platform for natural language interfaces as a service. Users are getting used to great search and conversational experiences thanks to big tech companies like Amazon and Google who are building compelling natural language applications like Alexa or Google assistant.
But the truth is that outside of these big players, 70% of site search engines are still unable to return relevant results in a very basic sense. So digital companies have almost 25% of visitors leaving due to a poor user experience. This is a disaster in engage-driven industries like ecommerce and media for instance.
We bridge the gap between ecommerce companies and the big tech players democratizing the AI technology necessary to compete. To do it we use a unique combination of knowledge graph data representation, NLP and Machine Learning.
(2) What inspired the creation of the startup?
I have PhD in Neuroscience and linguistics and Jacopo my cofounder is a data scientists specialized in knowledge representation for machine learning. Essentially we spent most of our adult life trying to understand how humans acquire knowledge and communicate it with natural languages.
At the same time, we live in a world where we still have to think in keywords to hack most of the search interfaces in our everyday life, because they are unable to understand us.
This is absurd (and I suspect harmful for our minds). We wanted to build machines that think like humans, not the other way round.
(3) What differentiates your startup from the competition?
Scalability. Everything hinges on our proprietary knowledge graph tech. Using knowledge instead of sheer data power we can scale better. The knowledge we acquire about industries, products and users gets centralized in a single and uniform semantic data platform. Thanks to that we can really democratize AI.
In this way, our customers get a solution that is optimized for their needs from day one: everything we know about everything become immediately available to each one of them, without waiting weeks or months of data ingestion.
(4) Who is the target market?
We now target big ecommerce sites and enterprises. Companies that need to make their UX great and need to understand the behaviour of their users at a deeper level, but lack the technology or the data volume to do that easily. We already work with billion-dollar companies like Leroy Merlin and Benetton.
(5) How did you grow your presence in your target market?
Our technological approach allow us to scale very efficiently within verticals, we go very deep into the them. We start getting some big players in one vertical, let’s say fashion, and gather data to learn the data structure of specific sectors. Then, because we can transfer the knowledge so efficiently, we can scale a strong network effect within the vertical. We already have good proof points of the effectiveness of this strategy, especially in the fashion vertical.
(6) What stage are you at?
We build the first end-to-end version of our product and got our first early adopters to use it. We are growing very fast and we are thrilled to be already working with $B companies and to bring real value to them: thanks to our tech they registered a 30% increase in the average order value after search and a 15% increase in the conversion rate after search.
(7) What are some of the biggest challenges that your startup have had to overcome?
We first had a few small clients to build our first prototype and then we got to bigger clients to build an end-to-end MVP. Moving from being a feature to being a solution has been a complex process. We were perceived as providers for smaller clients. Once we found the right clients who were willing to play ball, we were able to build a full AI solution.
(8) What is next for the startup?
Traction, traction, traction. We are now working on creating the right partnerships to go to market.
(9) Where would you like to be in the next 5 years?
Providing a unified knowledge platform for semantic search. We want to help millions of end users feel more human when they speak or type to communicate with a machine.
(10) If you had to give one piece of advice to an up and coming startup what would it be?
Your co-founders are the most priceless thing you have in your entrepreneurial life. Cherish that.
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