Bridge OPC UA and MQTT to scale your industrial data. Learn architectures, translation methods, and best practices for seamless OT-to-IT connectivity.
OT devices still run on Modbus RTU but your data architecture doesn't have to stop there. Learn how to bridge Modbus RTU to MQTT using a protocol gateway, without replacing legacy hardware.
HiveMQ's last six months: unified governance, enterprise security updates, improved diagnostics, and steady Edge and Kubernetes operator progress.
Learn how to stream CAN Bus data via MQTT for real-time asset monitoring. Covers CAN Bus protocol basics, decoding and edge integration step by step.
HiveMQ is now available on Microsoft Azure Marketplace. Buy through public plans or private offers and apply eligible purchases toward your MACC commitment.
Gartner warns that data quality challenges are consistently underestimated by manufacturing CIOs. Here is the three-activity framework for industrial AI data readiness, and how HiveMQ delivers each layer.
Why real-time data streaming is the missing foundation for industrial AI - and why enterprises that build it now will outpace those that wait.
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.
HiveMQ Edge supports OPC-UA and other M2M protocols. Learn how to install the Prosys OPC-UA simulation server and configure secure, bidirectional communication using Mutual TLS.
Industrial AI use cases like predictive maintenance and process optimization scale only when three data infrastructure layers work together.
Most manufacturing AI projects don't fail because of the model. They fail because the data backbone isn't ready. Here's what we heard from hundreds of manufacturers at Hannover Messe - and what it takes to fix it.
Three-layer data maturity path enables intelligent data centers: Data Streaming, Data Intelligence, and Agentic AI Orchestration for digital twins and autonomous control.
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.
Digital twins and Agentic AI enable autonomous data center operations: precision thermal control, stranded capacity recovery, and real-time optimization for AI workloads.
Learn how digital twins and agentic AI drive data center optimization by unifying telemetry, reducing uncertainty and unlocking stranded capacity. Read the blog.
Learn how Digital Twins and Agentic AI drive data center optimization. Solve power, thermal, and capacity challenges for AI-ready infrastructure. Read more.
AI workloads break legacy monitoring. Learn how MQTT, Unified Namespace, and HiveMQ deliver real-time telemetry streaming for AI-ready data center infrastructure.
Point-to-point integrations slow data center operations. Unified Namespace and event-driven architecture eliminate integration debt and enable faster site onboarding.
AI workloads break traditional billing. Real-time telemetry streaming via Unified Namespace delivers accurate, auditable billing and compliance for AI-era data centers.
Get a production-ready HiveMQ MQTT broker license in minutes. Two self-managed packages starting at $299/mo. Buy online, no sales call needed.
HiveMQ Partner Network (HPN) empowers SIs, VARs, and ISVs to scale enterprise IoT and industrial AI solutions with enablement, margin protection, and co-sell support.
Achieve global OEE across plants with a Unified Namespace. See how HiveMQ streams OT data, normalizes KPIs, and enables multi-site benchmarking.
HiveMQ is recognized by G2 as one of Germany's Best Software Companies for 2026. See why customers trust our industrial data platform.
Most industrial AI pilots succeed technically but fail to scale—because measurement breaks down across sites. Learn how to standardize OEE, downtime, and energy baselines so your AI ROI is defensible, comparable, and fundable enterprise-wide.
Industrial AI fails when OT, IT, and AI teams operate in silos. Learn how cross-functional ownership and a shared data layer align priorities and unlock scale.
Edge AI deployment challenges go beyond the model: compute constraints, connectivity gaps, lifecycle management, and security exposure at the production line.
Every industrial AI use case requires a custom data pipeline. Learn why legacy OT integration creates a hidden tax that compounds at scale and how to break the cycle.
Why 68% of industrial AI pilots fail to scale: non-replicable data pipelines, missing ROI baselines, and unclear ownership kill production deployment despite technical success.
Explore how human biases shape AI system architecture and why objectivity, intent design, and cultural transformation are essential for safe, effective agentic AI in manufacturing.
How to transform into an agentic AI company: encoding expertise, balancing innovation with reliability, and empowering teams through AI skills in the OT/IT convergence.
AI doesn’t replace experts; it codifies their knowledge into tools that empower everyone. Learn how AI enables a recursive self-improvement loop, turning domain expertise into an expertise flywheel.
