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"Enterprise AI should not be available to the big players only - it should be available to everyone."

- Christian Umbach, CEO & Co-Founder of Xapix

Xapix evolved from being a company highly focused on the automotive industry and became industry-agnostic. The company now provides a solution that is a match for most verticals. In this blog article, Christian will explain the why and how of Xapix recent development.

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Democratizing Enterprise AI - that is the bold new statement from Xapix. Can you explain what that means to you and how that evolved Chris?

We are seeing a new-way of thinking and building digital products across companies. Leaders like Amazon with their API-first mandate have set the basis back in 2002 and a few years later managed to build a comprehensive AI platform around it which we leverage every day now to enjoy services and computing at incredible scale.  

When I first advocated for the use of APIs in the airline industry and mobility around 2014, this was nascent but the industry followed through on establishing those platform technologies - yet some are still very much in starting mode. 

For teams this fundamentally enables a new form of connectivity across silos and partners now, yet to compete they want to ensure that machine learning is leveraged to scale faster through automation - for this the traditional rule-based systems fail. It’s simply too complex to manage and therefore both a performance and security risk. There is no way around Enterprise AI for companies, from a security, efficiency and success perspective. 

What is important to us: bringing down the price for teams, especially hidden champions without a budget to spend 10M Euros a year on an AI platform. For us it’s the democratization of the AI process in the enterprise world. As this process significantly helps our society realize key goals and advancements around sustainability because we are creating more transparency, and are acting on it. For SMEs and hidden champions both the greater advancement towards sustainability and further efficiency gains will be a game-changer and enable them to remain competitive. AI should not be available to the big players only. AI should be available to everyone.

Tell us a little bit more. Enterprise AI sounds like a big promise, but what are the core pillars from your perspective and why are they key to success?

Well trained PhDs to drive ML projects deliver zero value if they can’t bring their work into production. Today, most of them start failing by getting access to proper training data in the first place. What follows is usually a path of wasted time, money, and potential. Companies have learned the hard way, and no company is able to attract talent in this area without showing a clear path to allowing access to flowing data. 

APIs sit very much at the heart of this and are a central piece of making data flow across systems, we call this unifying data. Once data flows, actions can be taken on it - those can both be simple actions, or - more and more commonly - informed by machine learning algorithms. Teams are thereby moving from trained AI to applied AI. The actions that are being recommended now have to connect to the right target systems, an app, an ERP system, or a sensor unit. The ability to connect the enterprise is the key part to close the loop and enable efficient data and machine learning operations. 

If you are for something, you always also fight against something - what is your coat of arms, your Sauron?

We are looking for builders, teams who want to take their destiny into their own hands. There is a breed of companies that outsourced all development to Accenture or Deloitte. If you are doing that with things that are core to your future, it’s only a matter of time for teams to lose. We advocate for a product mindset and leadership in companies - and additionally a center of excellence that can help product teams overcome specific challenges or by leveraging the right tools. Enterprise AI is no future, it is there for anyone to use it today, but it’s not a big bang, rather a process of bringing in automation step by step as the enterprise becomes more and more connected. 

Going a bit deeper into the target groups you are aiming for, who is your ideal customer and to which people in the organization are you typically talking to?

We are aiming for the David of the industry that aims to beat Goliath - those who are smarter, more agile, more demanding and those who want to change the world for the better. We talk to the doers, the makers, the ones who take the lead and drive the change. At UBER years ago one of the mantras was “be an owner, not a renter”. I am fortunate to enable some of the most driven people across the industries with our technology. They see the power and use it to realize their own vision. 

Finally, we are industry agnostic which means that we develop an easy to use low code solution which anyone can use - independent of any industry. Of course, in some industries - like ecommerce - the pressure is a lot higher than say in real-estate to digitize systems. But what I love about working with our customers is that the nature and mindset of people, regardless of their industry, is quite similar. They want to shape the next generation of their industry, and not wait for others to shape it.

In this article on digital economy and new value creation we outlined how digital literacy in enterprises could be further accelerated.

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You said Xapix is industry agnostic by design, but let us know, are there specific verticals or sectors you are specifically excited about?

As you can imagine, the market for data operations tools is vast. We started in mobility 5 years ago as there has been an openness to collaborate with partners. By now, this mindset - and in some ways - pressure has arrived in other industries. 

Two very different examples, but with one common goal:

• Our customers in the German industrial Mittelstand - companies that have been globally successful for decades - are known to be in a position of power, some of them enjoy global market share in their niche upwards 50%. But in terms of digital - they are left behind. They got stuck, because what made them successful in the past, isn’t directly applicable to how you build and scale digital products. Yet, we are in a position to help bridge the gap and bring the latest technologies to them at a fraction of the price what industry giants today are spending. 

• Similarly, in the eCommerce aggregator space. Companies are rapidly aggregating Amazon and Shopify marketplace businesses into new conglomerates. Here the driver is speed and scale. Those companies are quickly reaching a level of complexity that cannot be mastered with people nor with current tooling. The ability to manage that complexity by giving them control over data streams, applying AI to manage those and reliably connect various enterprise systems helps them build out a new competitive edge.