A global leader in entertainment, gaming, and hospitality partnered with WSO2 to take the organization’s first step to becoming an agentic enterprise by building an intelligent solution that would transform how support teams operate. The solution, a virtual support engineer, automated a manual issue resolution process and reduced resolution times from 2 hours to 1 minute, helping to provide a better support experience for both customers and internal operations teams alike.

WSO2 will be present at the #INCYBERFORUM in Lille, France.
Come meet the team and discover how we help deliver access management the way it should be.
See you very soon!
Booth G2-08 (ID Forum area)

New index-based pricing model aims to offer governments worldwide equitable access to world class technology, software independence

How integration forms the connective tissue of human-AI collaboration and enables the next evolution of enterprise intelligence.

When we think of a typical API, part of a production-ready setup generally includes a cache. This cache allows for similar requests to be served without having to do the entire roundtrip. But when it comes to AI applications powered by large language models, traditional caching falls short. This is because queries to an AI endpoint may look different in terms of how things are worded or phrased but actually mean the same thing semantically. That's where semantic caching comes in: a technique that's become essential for running cost-effective and performant AI applications in production.

Getting APIs to work with AI has become one of the major themes in the API space recently. And that’s not surprising because APIs are at the core of an AI’s ability to reach out into the world, to get access to data and information, and to invoke commands and workflows to act. This was always what APIs were for, but in this article we will dive a little deeper what that evolution looks like, and what that means for API governance and management.