About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Kingland Extends AI Capability in Fourth-Generation Enterprise Software Platform

Subscribe to our newsletter

Kingland Systems continues to innovate with the fourth generation of its enterprise software platform. The platform provides artificial intelligence (AI) focused on data management, extended enterprise data management capabilities, new analytics, and cloud optimised DevOps software to support high performance software strategies. It also accelerates specific solution delivery by avoiding extensive customisation, providing 60% to 80% of core capability on Day 1, and focussing remaining time and budget on unique client requirements.

The platform uses a microservices architecture of more than 40 components to create client specific and cloud optimised solutions, and consists of four elements covering cognitive computing, data analytics, enterprise data management, and an enterprise applications foundation that accelerates project implementation and provides cloud optimisation, scalability and automated testing and deployment. The fourth-generation platform updates all these elements.

Tony Brownlee, a partner at Kingland, explains: “The fourth-generation platform formalises our cognitive computing capability and reimagines how master data management needs to operate on a modern platform. The microservices architecture helps our clients build, maintain and upgrade solutions.” He adds: “The platform is not a product, but key capabilities and components that solve clients’ problems and deliver quick, agile systems that can be maintained over years to come.”

The AI element of the platform is cloud-based and uses application programming interfaces (APIs) and software-as-a-service (SaaS) delivery to integrate with legacy systems. Its focus is on data management, data collection, and business process automation, and it has been enhanced in response to client requests to unlock data in legacy documents.

Brownlee says: “Our AI engine is very fast. It can read a 300-page document and extract data in seconds. This helps users discover and maximise new data. Typically, the data covers customers, legal entities and individuals, noting their location, services they have received, how they are related to each other, and news about issues such as mergers and acquisitions or bankruptcy.”

The company is also experiencing growing demand for cloud-based machine learning, particularly for risk, credit risk, transaction processing, clearing and settlement, and compliance. Brownlee comments: “Clients want more machine learning and the ability to load diverse types of data. The goal is to deliver data faster than can be done internally at a lower cost.”

While Kingland continues to invest in its technology and deployments across a number of industries, Brownlee concludes: “The fourth generation is something to celebrate for us. It can solve some significant problems in the world.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Building a Semantic Layer for Your Enterprise Data Estate

Date: 8 September 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes The democratisation of data has encouraged engineers to think about how to make their data estates more accessible and useable for non-technical business end-users. Translating intention into data action requires careful configuration that enables consumers to mine insight, analytics...

BLOG

Embrace the Threat: How Software Firms Can Head Off ‘SaaS-pocalypse’

Recent stock market losses among software providers have prompted some analysts to predict a coming “SaaS-pocalypse” as software companies are threatened by artificial intelligence that can write code and build software quickly and cheaply. The doomsayers may be premature, however. While AI undoubtedly has the ability to supplant some of those firms, it also presents...

EVENT

Data Management Summit London

Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...