The biggest challenge for enterprises in the rapidly evolving world of Generative AI isn’t just building “smarter” LLMs or agents — it’s securely connecting that AI to the decades of business logic and data locked away in enterprise systems. How do you let an AI agent interact with your Salesforce data, your Kafka topics, or your internal databases without rewriting everything or creating a massive security hole? It turns out the answer may already be running in your organization.
Continue reading ❯
CAMELAI
In the rapidly evolving landscape of AI-powered applications, the ability to process and understand documents has become increasingly crucial. Whether you’re dealing with PDFs, Word documents, or PowerPoint presentations, extracting meaningful insights from unstructured data is a challenge many developers face daily. In this post, we’ll explore how Apache Camel’s new AI components enable developers to build sophisticated RAG (Retrieval Augmented Generation) pipelines with minimal code. We’ll combine the power of Docling for document conversion with LangChain4j for AI orchestration, all orchestrated through Camel’s YAML DSL.
Continue reading ❯
CAMELAI
Apache Camel 4.15 has just been released. This release introduces a set of new features and noticeable improvements that we will cover in this blog post. Camel Core You can now easier extend Camel via 3d-party dependencies via Java ServiceLoader using the ContextServicePlugin SPI. You can add custom sensitive keys to camel.main.additionalSensitiveKeywords which Camel will mask in logging. Camel JBang camel debug now also supports debugging Camel Quarkus applications, by executing camel debug pom.
Continue reading ❯
RELEASES