Act: How to operationalize data for governed agentic AI-driven action
Learn how agentic AI in manufacturing turns trusted operational insight into safe action, with scoped agent roles, human approval and a full audit trail.
Data governance for trusted manufacturing intelligence
How data governance builds trusted manufacturing intelligence: broker-level policy enforcement, access control and lineage across every MQTT data stream.
Industrial Data Intelligence Platform | HiveMQ
Turn industrial data into trusted, governed intelligence with a Unified Namespace built for people and AI. See how HiveMQ Data Intelligence works.
Connect: Building a real-time data backbone for data accessibility
See how a real-time data backbone built on MQTT connects plant floor and enterprise systems, giving agentic AI the operational visibility it needs to act.
Building a scalable data foundation for real-time operational intelligence
A technical white paper on the four-stage Connect, Contextualize, Analyze, Act architecture for turning fragmented manufacturing data into real-time operational intelligence and a governed foundation for agentic AI.
Functional models and agentic AI data requirements in UNS
Agentic AI data requirements go beyond telemetry. See how functional models in a Unified Namespace ground safe, accurate reasoning for industrial AI agents.
Turning UNS use cases into concrete agentic AI use cases
Turn your Unified Namespace into production-ready agentic AI for manufacturing. A four-criteria framework to scope, govern and measure your first agent.
Securing agentic AI in OT authentication and authorization for factory agents
Explore how to secure agentic AI in OT with verifiable agent identity, least-privilege authorization, & broker-level command enforcement for factory agents.
Agentic scheduling: Adaptive shop floor planning on the UNS
Learn how agentic scheduling on the Unified Namespace turns shop-floor disruptions into real-time reschedules, with HiveMQ guiding the way.
From analytics to action: Wiring agentic decisions back into the UNS
Wire agentic decisions back into the Unified Namespace as governed, auditable topics, with HiveMQ enforcing guardrails at the broker level.
MQTT vs REST vs message queues: Which data architecture is best for industrial AI?
Industrial AI requires continuous, reliable data streams but not every integration approach was designed for that. Compare MQTT, REST integrations and traditional message queues to understand which architecture scales best for AI workloads.
From data chaos to agent-ready order in smart manufacturing using UNS
Data chaos costs manufacturers 15-25% of operating budgets. See how reliable streaming, semantic context and governance make operational data agent-ready.
The business case for an agent-ready unified namespace in industrial AI
An agent-ready Unified Namespace cuts integration costs and gives AI agents the context to reason and act safely. See the manufacturing business case.
Real-time vs. historical data: Why industrial AI needs both
Industrial AI needs real-time and historical data together, not one or the other. See why a live streaming layer gives AI inference the context it is missing.
From Distributed Data Intelligence to Distributed Agentic Intelligence in manufacturing
Distributed Data Intelligence (DDI) provides the semantic foundation and governance framework that distributed AI agents need to operate safely in manufacturing environments.
Data interoperability: The foundation for AI agents in manufacturing
Interoperable, semantically rich operational data is the prerequisite for deploying AI agents that can reason and act safely across manufacturing systems.
Turn industrial data into operational intelligence
As Industrial AI moves from experimentation to production, organizations are discovering that architectures built for historical analytics struggle to deliver the trusted, real-time operational intelligence AI requires.
Why Intelligence Needs to Be Distributed, Not Centralized
On-demand - Explore why intelligence needs to move to where operational data already lives.
AI in Industrial Automation vs Traditional Automation: What Actually Changes?
Traditional automation runs fixed programs. AI-driven automation adapts in real time. Learn what that means for your data pipelines and OT architecture.
CXO FAQs: What Agentic AI Demands from Your Unified Namespace
A Unified Namespace is the prerequisite for agentic AI in manufacturing. Learn what CXOs must build before deploying AI agents on operational data.
Industrial AI for Oil & Gas: The Data Backbone Underneath
Industrial AI in oil and gas stalls on the data layer, not the model. HiveMQ on the operational data backbone oil and gas leaders need ahead of DES Summit Madrid.
A Data Maturity Path to Intelligent Data Center Optimization
Three-layer data maturity path enables intelligent data centers: Data Streaming, Data Intelligence, and Agentic AI Orchestration for digital twins and autonomous control.
Why Traditional Data Center Infrastructure Falls Short
Point-to-point integrations silo data and block real-time control. Learn why unified, event-driven architecture enables digital twins and Agentic AI in data centers.
Optimizing Data Center Operations with Digital Twins and Agentic AI
Optimize data center operations with digital twins and agentic AI. Improve efficiency, capacity, and real-time decision-making.