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Kingland Upgrades Fourth Generation Enterprise Software Platform

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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.”

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