Introduction to TrustyAI and Drools Explainability is a crucial aspect in modern AI and decision services work; recent laws entitle any person subject to automated decisions to explanations of the intuition behind said decisions. Moreover, people are more likely to trust the decisions of explained models compared to unexplained models (Kim et al., 2022). Furthermore,Read more →
Following up from a previous blog post about integrating Drools with the Open Prediction Service, in this new post we want to share the current results from another exploration work: this time integrating Drools with research on Transparent Machine Learning by IBM. Introduction Transparency is a key requirement in many business sectors, from FSI (FinancialRead more →
This post summarises the current design of REST endpoints which are automatically generated and made available, when using DMN model assets in a Kogito application. This work was finalised as part of KOGITO-2840. Introduction For each DMN model in a Kogito application, a collection of REST endpoints is automatically code generated based on the contentRead more →
For the last few months, here at KIE team we’ve been hard at work. Today I am proud to announce that our cloud-native business automation platform is hitting a major milestone. Today we release Kogito 1.0! Kogito includes best-of-class support for the battle-tested engines of the KIE platform: the Drools rule language and decision platform, the jBPM workflow and process automation engine, the OptaPlanner constraint satisfaction solver; and it bringsRead more →
