Company Blog

So why Iowa? It’s a question we get often from executives around the world. For such an innovative company of software architects, artificial intelligence engineers, and data SMEs, how and why do we do it from Iowa? The answer is quite strategic, and I'll go over four of the key reasons we choose to grow Kingland from Iowa. 

Last week leading banks, broker dealers, and regulators gathered in New York for DTCC’s third annual Fintech Symposium. This is always a must attend event for Kingland as its incredibly well run and covers many of the emerging trends in the industry in an afternoon.  DTCC’s perspective is critical as they sit at the cross roads of the sell side, buy side, and global regulatory environment, so if an issue is on the table, there’s a strong reason. 

As the Consolidated Audit Trail (CAT) saga continues to unfold, there is continued uncertainty throughout the industry. When are the reporting deadlines? Are the specifications published and final? Are we reporting personally identifiable information or not? All of these questions are clearly on the table, being discussed by the SEC, SROs, and firms throughout the industry. As the weeks go by in 2018, we expect the answers to these questions to become clear. 

For years and years, regulatory and legal requirements have created hundreds if not thousands of processes that require companies to capture information in documents or records. This information includes details about their customers, suppliers, market activity, and many other facets of their business. I don't know a company on the planet that really values all of this documentation. However, in the era of Artificial Intelligence and Natural Language Processing, we're discovering that all of this documentation may be a goldmine of data for these large enterprises. 

I loved playing with LEGO pieces as a child. I remember building specific things such as castles, vehicles and helicopters from the different shapes and sizes. I may have started to build those models a time or two according to the directions before I started using the blocks to build other things, things not imagined by the designers of the sets. The innumerable outcomes of creating things with LEGO blocks allowed me to imagine and design numerous 'products' for me and my friends. 

Blue. Green. Red. Black. No, I'm not just talking about colors. I'm talking about a specific deployment technique we use at Kingland that allows for near zero downtime and the ability to easily rollback to a previous release if there are too many issues with the latest release. 

Blue/green is a deployment technique where there are two identical sets of infrastructure. One set/environment - blue - has the current production release installed. The other set/environment - green - has the next production release installed. To keep things running smooth, a load balancer sits in front of the two environments and is pointed at the blue environment. When the green environment has the latest release installed, has been smoke tested and is ready for production, the load balancer is changed to point to the green environment. Any transactions occurring in the blue environment are allowed to finish, but all new transactions are directed to the green environment. In the event there is an issue with the release in the green environment, the release is rolled back by changing the load balancer to point to the blue environment.

At Kingland, we use a variety of Artificial Intelligence (AI) techniques for text analysis as we build cognitive and enterprise data management solutions. One of the most sophisticated is the neural network. Inspired by (but certainly not the same as) human biology, neural networks can learn to answer questions about complex data by observing and storing examples of subtle patterns in the connections between nodes, which are loosely analogous to neurons in the human brain. Most neural networks have multiple layers, with information flowing from one layer to the next (and back again in some cases), often transforming the input into more and more abstract representations as it progresses through the layers.

In the last 30 days I've had many conversations with executives about cognitive, or artificial intelligence (AI) capabilities. I think we've made tremendous progress with our cognitive computing suite at Kingland over the last 7 years and it's fun to show people what we've done and where we're headed. The surprising thing to me, though, is the amount of skepticism I still hear from these leaders. When it comes to AI, there's almost a "too good to be true" cautiousness in the discussions. I think this is driven from the sheer volume of attention AI is getting as these leaders are asked daily to join the "AI Club". At the same time, though, I hear an incredible amount of optimism. Executives are thinking "maybe AI is one of the key investments I need to make to really make a difference." The efficiency, the automation, the chance to deliver something innovative for their company; all of these breed optimism.

I'd like to explore both sides of this skepticism / optimism coin. Let's look at one of the most popular questions I get:  "So...is that really AI"? 

There is a lot of hype around Cognitive Computing. In the past month, a Google search discovered nearly 16,000 articles devoted to the topic. For perspective on the hype, Forbes contributor Bernard Marr wrote, "Today another revolution is underway with potentially even further reaching consequences... Cognitive computing, machine learning, natural language processing - different terms have emerged as development of the technology has progressed in recent years. But they all encapsulated the idea that machines could one day be taught to learn how to adapt by themselves..." 

In prior posts, I have discussed what microservices are, how the cloud enables microservices, and how microservice architecture is a great fit for our agile project approach. So you may ask yourself, “sounds like microservices is a great way for Kingland to develop software, but what is in it for me as a potential customer?”