Home IssueArtificial Intelligence 5 Q’s with Nikolas Kairinos, founder and CEO of Soffos

5 Q’s with Nikolas Kairinos, founder and CEO of Soffos

by Gillian Diebold

The Center for Data Innovation spoke with Nikolas Kairinos, founder and CEO of Soffos, an Austin-based startup that builds low-code AI applications. Kairinos spoke about use cases for natural language processing and conversational AI and the technology’s impact on the business world. 

Gillian Diebold: Soffos provides businesses with low-code solutions for developing applications. What does this mean? 

Nikolas Kairinos: In essence, low- and no-code solutions democratize the application development process, allowing businesses to take a user-friendly approach when designing products instead of programming them the old-fashioned way in code. These solutions can be leveraged by technical employees with coding expertise and non-IT employees alike, making it possible for organizations to build manageable and fast applications that align perfectly with their offerings in an accessible and cost-effective manner. Better still, they enable firms to innovate at a much faster pace, thanks to the ‘drag and drop’ design of low-code platforms that enterprise and citizen developers can use to connect application components.

This approach is exciting because it makes it possible for a much larger number of businesses to push the innovation needle forward and bring applications to market in half the time. In the past, the task of creating any application, let alone one powered by artificial intelligence (AI) or natural language processing (NLP), was solely the reserve of software developers and technical employees with the coding skills required to create apps from scratch. 

If you can’t afford in-house expertise, then this is no longer an obstacle to pushing ahead with digital transformation initiatives. Our solution provides businesses with the ‘building blocks’ and core technologies required to build countless novel NLP applications without writing a single line of code – from learning and assessment tools to knowledge management platforms and beyond. It is fantastic to see that many firms are already expanding their horizons into the AI arena by taking advantage of powerful new solutions – we hope that we can support many of them along the way.

Diebold: Can you explain the technology behind Soffos?

Kairinos: NLP and conversational AI are at the heart of everything Soffos does. Our technology draws upon a central framework of neuro-symbolic NLPthis refers to AI that improves how a neural network arrives at a decision by adding classical rules-based AI in the process. The components of this framework enable our customers to achieve various key objectives depending on their organization’s specific needs. 

Using this technology, we offer a suite of unique application programming interfaces (APIs) so businesses can choose the natural language functionalities they would like to include in their applications. To give you an idea of the kinds of products our clients can build, to date, we have helped companies build conversational AI agents to support sales and lead generation, patient management applications for those in the healthcare arena, and state-of-the-art learning tools. But the opportunities are infinite. Our development work in advanced NLP technology can be of use for almost anything related to NLP, conversational AI, cognitive AI, and related fields.

Diebold: How is natural language processing (NLP) impacting the business world?

Kairinos: There is rarely a day that goes by where I don’t read another new headline about how NLP is transforming the business world. I recently read an article explaining how Bloomberg and other financial services firms are using the technology to augment how customers interact with their business. I would go as far as saying that NLP is the next frontier in AI for enterprises, and there is plenty of research to back this up. Market research currently indicates that businesses are crying out for enhanced customer support systems to improve the customer journey and that plenty are integrating AI to do so. Beyond this, the global conversational AI market is developing at a high Compound Annual Growth Rate (CAGR), with some predictions suggesting that it will triple in size by 2030. 

At the crux of these trends is the fact that NLP-powered applications have the potential to help businesses interact better with their customer base, scale up and ultimately boost their revenue. Already, the use-cases are building rapidly for those looking to tap into NLP, but perhaps its primary advantage is the ability to sort through vast amounts of unstructured data or text quickly without having to rely on unwieldy keyword search or statistical text mining tools.

Diebold: Apart from a business setting, where else can low-code AI have an impact?

Kairinos: In the spirit of true citizen development, I predict that the movement could break out of the business world and into the realm of non-governmental organizations (NGOs), charities, and community groups. With a low-code approach, they can easily build apps that best suit the needs of their causes, which would really give meaning to the low-code trend.

Diebold: What does the future look like for NLP and low-code solutions? 

Kairinos: Chances are, if you own a home assistant, a smartphone, or a Gmail account, then you are already familiar with the trajectory that NLP is likely to follow. As more businesses deploy low-code solutions and NLP to drive their operations, bolster their customer journeys and simplify data-intensive tasks, expect new consumer-focused products to emerge that will further augment translation and search engine optimization, as well as further advances in sentiment analysis.

As the technology matures and NLP’s proficiency in sentiment analysis and understanding of human language improves, computers will be able to understand the words we say and what we mean when we say them. Eventually, they’ll even be able to predict what we are going to say. Whilst the applications of this kind of machine are not clear at the moment, the possibilities of this technology are endless.

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