Artificial Intelligence

Welcome to the age where artificial intelligence is transforming predictive maintenance from an alarm system into something that resembles intelligence—particularly for companies operating in the oil and gas sector.

To make AI agents work in production, enterprises need a new architecture—one built on real-time data, governance, and event-driven orchestration.

In this post, I’ll show you how to set up the Solace Event Portal  Model Context Protocol (MCP) server with a tool like Claude Code to automatically analyze your code,...

A2A Summit made one thing clear: the agent era has arrived, and enterprises are rapidly moving from experimentation to orchestration.

In Solace Agent Mesh, an agent is the main processing unit that receives prompts, executes a couple of LLM-supported actions, and gives the response back to the original requestor.

In the world of AI, agents, and dynamic coordination, EDA is a necessity. But to let them understand, reason, and act you must think beyond request/reply and standard EDA, you...

The August 2025 Gartner® report, Innovation Insight: AI Agent Development Frameworks analyzes this evolving space, explaining the drivers behind rapid adoption, benefits and use cases. and how organizations can choose...

The convergence of edge computing and artificial intelligence demands event-driven systems that enable the evolution from centralized AI tools to distributed autonomous intelligence systems.

The competitive edge in AI isn’t just in better models or smarter prompts — it’s in connecting AI to the live, operational pulse of the business from day one.

In this article, I’ll show you how to create AI agents and run them with Solace Agent Mesh—fast to build, easy to scale, and ready for real-world use.

When it comes to agentic AI, we can either learn from the microservices journey and adopt EDA from the start, or repeat history and spend years untangling tightly-coupled systems.