Turn real-time manufacturing plant data into operational intelligence with the new HiveMQ Platform
HiveMQ's new platform helps manufacturers reduce downtime, improve efficiency and replicate proven operational improvements by getting the data foundation right.
HiveMQ Team, Sep 9, 2026
From machine data to action: How HiveMQ Platform works
HiveMQ Platform turns fragmented plant data into real-time, trustworthy intelligence, so you catch problems while the line is still running and get your AI pilots into production.
Shashank Sharma, Sep 8, 2026
140 billion data points a day, zero lost: why MQTT is the energy data backbone
MQTT moves 140 billion energy data points a day with zero loss. See why event-driven transport, not polling or batch, is what real-time energy operations need.
Anthony Olazabal, Sep 8, 2026
A new chapter for the HiveMQ broker: What the HiveMQ 4.55 LTS means for your business
Discover what HiveMQ 4.55 LTS brings to your business, with long-term support, stronger security, simpler operations, and a platform built to scale.
HiveMQ Team, Sep 4, 2026
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.
Kudzai Manditereza, Sep 3, 2026
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.
Kudzai Manditereza, Sep 2, 2026
Safe AI action in industrial operations: Your architecture sets the ceiling
Trusted delegation sets the rules for safe AI action in industrial operations, but your data architecture decides how far you can actually delegate it.
Shashank Sharma, Sep 1, 2026
Agentic manufacturing: why the Unified Namespace comes first
Agentic manufacturing turns real-time operational data into governed AI action. See how a Unified Namespace makes it possible, with human oversight built in.
Kudzai Manditereza, Aug 28, 2026
Analyze: Turning contextualized data into actionable real-time intelligence
Learn how an operational intelligence platform turns contextualized industrial data into real-time, governed insight for teams, applications and AI agents.
Kudzai Manditereza, Aug 27, 2026
Why clean data is the real competitive advantage in industrial AI
Clean industrial data gives AI the context and governance it needs to scale. Learn how manufacturers can build a trusted data foundation beyond pilots.
HiveMQ Team, Aug 26, 2026
A Wind Farm Is Not a Factory Line: Designing a Namespace for Energy Assets
Energy companies should not copy a manufacturing Unified Namespace. Learn how to design an energy-specific namespace for assets, operations, and data.
Anthony Olazabal, Aug 24, 2026
Contextualize: Turning data into understandable operational information
Learn how industrial data contextualization turns connected data into trusted, governed information that people, applications and AI agents can act on.
Kudzai Manditereza, Aug 21, 2026
Contextual modeling strategies to reduce manufacturing data volume
Efficient contextual modeling reduces manufacturing data volume without losing insight, using report-by-exception and Semantic Graph design.
Kudzai Manditereza, Aug 20, 2026
Why do industrial AI teams still spend so much time on data preparation?
Industrial AI teams lose most of their time to data preparation. The real fix isn't more data engineering. It's closing the architecture gap upstream.
Shashank Sharma, Aug 19, 2026
How to win an Industrial Data Innovation Award
Enter the Industrial Data Innovation Awards - recognizing excellence in MQTT, industrial AI and industrial data innovation.
HiveMQ Team, Aug 17, 2026
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.
Kudzai Manditereza, Aug 13, 2026
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.
Kudzai Manditereza, Aug 11, 2026
Why energy companies need a unified namespace now
Energy operators don't lack data, they lack trust in it. Discover why a unified namespace fixes fragmented KPIs, and where it genuinely isn't needed yet.
Anthony Olazabal, Aug 10, 2026
Why point-to-point data integration breaks industrial AI
Point-to-point integration buckles under industrial AI. Event-driven architecture and a Unified Namespace fix the integration complexity causing AI failure.
Shashank Sharma, Aug 7, 2026
Why distributed intelligence must replace centralized data
Why centralizing operational data slows industrial AI at scale, and how a distributed intelligence model helps teams act on operational data in real time.
Kudzai Manditereza, Aug 6, 2026
A 12-week plan to make manufacturing data agent-ready using UNS
A 12-week plan turns siloed manufacturing data into an agent-ready Unified Namespace, delivering measurable ROI at every phase. See where to start today.
Kudzai Manditereza, Aug 5, 2026
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.
Kudzai Manditereza, Aug 4, 2026
Streaming sensor data to an Edge AI model over MQTT with C#
Learn how to stream sensor data to an edge AI model over MQTT in C#, using MQTT 5 flow control and manual acknowledgment to set the model's intake rate.
Peter Giacomo Lombardo, Jul 30, 2026
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.
Kudzai Manditereza, Jul 28, 2026
Data without context is just noise: The case for semantic operational data
Raw sensor data lacks context. See why semantic operational data, discovery and governance are the three capabilities that make industrial AI models reliable.
Shashank Sharma, Jul 27, 2026