Real-Time Fraud Detection in Java with Kafka Streams and Vector Similarity
How Java, Kafka Streams, and MongoDB vector search combine to catch fraud in real time, from rule-based guardrails to behavioral similarity scoring.
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69 articles on AI and machine learning in Java.
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How Java, Kafka Streams, and MongoDB vector search combine to catch fraud in real time, from rule-based guardrails to behavioral similarity scoring.
Ricardo Mello
380 views
Viktoria Evdokimova
253 viewsSomewhere in every coding agent there is an HTTP client. Claude Code, Codex, Cursor, Cline, OpenCode: strip away the terminal UI or the …

Viktoria Evdokimova
399 viewsA detailed report reads like proof. The agent lists the files it touched, names the branch, quotes a commit hash, adds a test count and …

Most Java teams who want a machine learning model in production end up standing up a Python service and calling it over HTTP. That works, …

Miro Wengner
3,885 viewsOver the past two weeks, the field of artificial intelligence has continued its remarkable pace of advancement. As AI becomes increasingly …

Geertjan Wielenga
668 viewsCan an agent initiate a payment, decline a loan, or file a compliance report in a way that's deterministic enough to defend?

Mahendra Rao B
1,783 viewsLearn how to use Spring AI SDK with the Amazon Bedrock AgentCore to build scalable AI-powered applications.

Miro Wengner
8,373 viewsOver the past two weeks, the field of artificial intelligence has continued its remarkable pace of advancement. As AI becomes increasingly …

Miro Wengner
6,950 viewsTwo weeks have passed and a lot have been happening on the field of artificial-intelligence. Two weeks have passed and a lot has been …

Michal Maléř
2,916 viewsx402, ERC-8004, A2A, and The Next Wave of AI Commerce: Do AI Agents Dream of Electric Langoustines? A Blade Runner riff for a world where …

Bruno Borges
3,369 viewsEvery Java developer has been there. Something breaks, and the first instinct is to litter the code with System.out.println(">>> HERE…

Zikani Nyirenda Mwase
2,118 viewsSee how to use machine learning in java by building a Spring Boot API for Spam Detection using the ONNX Runtime for Java.

Miro Wengner
9,534 viewsTwo weeks have passed, and it is time to present a new collection of readings that may shape developments, utilization or ideas in the field …

Miro Wengner
6,268 viewsFirst of all, Happy New Year 2026! This year is designated in the Chinese Calendar as the Year of the Fire Horse (starting on February 17.). …

Nehal Gajraj
2,325 viewsThe days of brittle, monolithic prompts and plug-and-play model swaps are over. Instead, modular prompting, paired with deliberate model …

Ewa Szyszka
3,382 viewsInstead of chasing higher benchmark scores or relying on traditional metrics, CodeRabbit focuses on how AI systems actually perform in live …

Miro Wengner
9,960 viewsFourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of …

Miro Wengner
11,611 viewsFourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of …

Miro Wengner
9,476 viewsA few months ago, I launched the AI Newsletter to provide a minimally biased perspective on the growing challenges surrounding artificial …

Miro Wengner
11,072 viewsThis newsletter focuses on examining how AI enhances productivity through enterprise studies, agentic system architecture, attack vectors, …

Miro Wengner
7,358 viewsFourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of …

Miro Wengner
9,836 viewsFourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of …

Miro Wengner
10,854 viewsFourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of …

Miro Wengner
8,634 viewsThe name “Stochastic AI Agility” suggests that the output of using AI-LLM definitely contributes to the goal, but the impact may not be …

Miro Wengner
7,014 views14 days have passed and it's time for a new batch of readings that could shape developments in the field of artificial intelligence.

Miro Wengner
4,434 viewsThe current newsletter vol.3, brings a collection of valuable articles focusing on challenges that are commonly reported through reported …

Jonathan Ellis
5,341 viewsThe Brokk Power Ranking is a new open-source coding benchmark, featuring 93 tasks from large, real-world codebases.

Miro Wengner
9,225 viewsThe JC-AI Newsletter Vol.2 brings again a very interesting collection of articles worth considering.

A N M Bazlur Rahman
4,147 viewsLearn how to build secure AI applications using LangChain4j guardrails in Spring Boot. Implement input/output validation, prevent prompt …
For Java developers, CodeRabbit offers specialized analysis that understands Java syntax, best practices, and common patterns.

Miro Wengner
15,183 viewsAfter brainstorming, our Java Champion Education group agreed to create a newsletter with a 14 days cadence.

Tim Kelly
4,480 viewsLet's use MongoDB with LangChain4j to create a simple RAG application. LangChain4j abstracted away a lot of the steps along the way, from …
David Parry
37,025 viewsGet hands-on experience with the exact code examined in this article, along with exercises, debugging techniques, and best practices for …

Karin Lauria
2,680 viewsWe’re in the middle of a fundamental change in how enterprise software works. In the next decade, your database will become your AI.

Raphael De Lio
8,840 viewsLearn how I improved zero-shot classification in Deep Java Library (DJL) by fixing token_type_ids support, optimizing logit handling, and …

Jennifer Reif
6,672 viewsIn this blog post, we'll explore the different layers of RAG, including vector RAG, graph RAG, and agents.

Jennifer Reif
10,245 viewsExplore a few introductory concepts around Retrieval Augmented Generation (RAG), why it exists and the problems it solves.

Zoran Sevarac
8,914 viewsJefferson Lab is leveraging Java-based AI to overcome one of the most computationally intense challenges in modern science.

A N M Bazlur Rahman
3,375 viewsMy Journey Creating an AI-Powered Form Filler with RAG, LangChain4j, and Ollama

This first online Foojay Webinar highlights Java's place in the AI revolution, focusing on exploring AI/ML using pure Java tools.

This first online Foojay Webinar will highlight Java's place in the AI Revolution, focusing on Exploring AI/ML Using Pure Java Tools.

Experience AI technology in Jakarta EE and MicroProfile applications that run on Open Liberty by using LangChain4j APIs.

Frank Delporte
6,956 viewsIn this Foojay podcast, we enter the world of mathematics by discussing Vectors and how they are crucial for AI and machine learning.

In this episode you'll hear Simon Martinelli, Nicolas Fränkel, Marcus Hellberg, Rick Ossendrijver, and Abdel Sghiouar.

On Tuesday, May 14th, the Foojay Podcast went live at the JCON conference in Cologne, Germany, to talk with speakers and visitors about all …

Jansen Ang
12,238 viewsDiscover how to build a smart home assistant using Langchain4j and Raspberry Pi, featuring capabilities such as question-answering with RAG, …

Frank Delporte
21,662 viewsThe way we search for information and develop software has changed a lot since then as the use of Artificial Intelligence suddenly became a …

Guillaume Laforge
6,581 viewsLately, for my Generative AI powered Java apps, I've used the Gemini multimodal large language model from Google. But there's also Gemma, …

Frank Delporte
19,966 viewsLet's use an existing documentation set as the data for a ChatGPT-like application, created with JavaFX and LangChain4J.

Soham Dasgupta
6,411 viewsRecap of spending the day in AI and Machine Learning Developer Room at FOSDEM’24!

Johannes Bechberger
5,787 viewsLearn about the website that gives an overview of JFR events, with descriptions from the OpenJDK, their properties, examples, …

Marit van Dijk
4,366 viewsDon’t miss the online JetBrains AI launch event, where we'll release our AI-powered coding companion, JetBrains AI Assistant.

Marit van Dijk
3,315 viewsIn this session, Anton Arhipov will demonstrate the capabilities of AI Assistant in IntelliJ IDEA. You will learn how the tool helps you …

Steve Poole
3,870 viewsAI and Java what is there?, what can it do?, what do we want it to do?, Asking for your input readers. Share your thoughts at Foojay.io

Simon Verhoeven
14,137 viewsThorough, practical examples using a new & rapidly evolving tool. Pro or contra, it's a very worthwhile read.

Frank Delporte
3,650 viewsThe first week of October, the 20th edition of Devoxx took place in Antwerp, Belgium. I got the opportunity to walk around with a microphone …

Jonathan Ellis
13,035 viewsJVector is a pure Java embedded vector search engine that powers DataStax Astra and is being added to Apache Cassandra.

Frank Delporte
4,115 viewsEvery conference has several talks about these technologies, and on Foojay, you can find multiple posts about it. Let's take a look at it …

Antonio Perrone
5,798 viewsWe explore image generation with Quarkus and OpenAI using the new REST Client Reactive to invoke the OpenAI DALL.E API.

Geoffrey De Smet
8,803 viewsTimefold continues OptaPlanner, open source project optimizing operational planning, saving thousands of organizations time, money, …

Denis Magda
44,600 viewsLearn how to integrate the ChatGPT engine into your Java applications in a scalable way by sending prompts to the engine only when …

Zoran Sevarac
5,345 viewsFor more complex deep learning challenges, more data, and need better performance, take a look at Deep Netts Professional Edition.

Zoran Sevarac
6,205 viewsLearn how to make it easy to quickly start using deep learning and to integrate deep learning into existing Java applications.

Gagik Gavalian
5,075 viewsWe use the Deep Netts library to implement our neural networks to do track classification, using Multi-Layer Perceptron (MLP) Neural …
Learn about Deep Netts, a lightweight Java-native library, easy to learn, and solves many technical challenges related to ML.

Tremendous potential for Deep Netts in the drug discovery pipeline and it is necessary to share its existence with the scientific community!

Nguyen Pham
4,210 viewsThe goal of this research is to sensitize small and medium-sized enterprises (SMEs) to the topic of AI with the help of Open Source Tools.

Kevin Farnham
3,770 viewsI spoke with Fabiane recently about Tail Target, its objectives, the theory behind it, and the underlying technology. Read on!
Zoran Sevarac
4,130 viewsSo you're a Java developer and you want to do some machine learning. Meet JSR 381, a standard Java API for Visual Recognition using machine …