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 Upgrades Fourth Generation Enterprise Software Platform

Subscribe to our newsletter

Kingland continues to develop the fourth-generation enterprise software platform it brought to market last year with the delivery of zero downtime deployment of platform components, improved performance, availability and security of microservices transactions, and refined artificial intelligence (AI) and natural language processing (NLP) capabilities used to extract data from PDF documents.

The introduction of the fourth-generation platform was a step change for Kingland and its customers, providing a microservices architecture, extended enterprise data management, additional analytics, cloud optimised DevOps, accelerated solution delivery, and an AI engine able to ready a 300-page document and extract data in seconds.

The company’s latest developments build on these capabilities. Jason Toyne, chief technology officer at Kingland, explains: “We’ve enhanced the platform’s ability to discover and extract data from machine readable and scanned PDF documents, allowing organisations to improve the accuracy and efficiency of text mining and analysis. This is another important step in our commitment to rolling out data focused AI and NLP capabilities.”

The platform uses microservices as part of its more than 40 complementary components and focuses on device independent software that can be reached from anywhere and can keep up with changing needs of users. The microservices are integral to helping users discover data and gain additional context around complex and unique enterprise data requirements. They offer the benefits of operational cost savings, reduced revision risk due to less code, and improved scalability.

Platform updates include:

  • Cross microservices transaction support – improved transaction management increases data consistency
  • Container based deployments and scaling – new DevSecOps capabilities allow seamless scaling and zero downtime deployment of all fourth-generation platform components
  • Collector data lake – a framework that allows the combination of both batch and stream-based data to be used in AI and enterprise data management solutions.

Toyne concludes: “With more than 25 years of industry knowledge, the Kingland team understands how to reduce risk associated with the variability of unstructured data. By providing industry specific solutions, our clients are discovering, collecting and making better decisions from all their data, from any source.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: An Agile Approach to Investment Management Platforms for Private Markets and the Total Portfolio View

Data and operations professionals at private market institutions face significant data and analytical challenges managing private assets data. With investors clamouring for advice and analysis of private markets in their search for returns, investment managers are looking at ways to gain a more meaningful view of risk and performance across all asset types held by...

BLOG

GLEIF Begins a New Decade in Growth Mode

The Global Legal Identifier Foundation (GLEIF) enters its second decade this month with its novel system of identifiers for everything from companies and their financial instruments to real assets fast becoming a global standard. While the next five years are expected to see yet more entities join the GLEIF’s open data project, the organisation’s immediate...

EVENT

Data Management Summit New York City

Now in its 15th year the Data Management Summit NYC brings together the North American 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: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...