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EMQ is an open-source IoT data infrastructure software provider, delivering the world's leading cloud-native MQTT-based IoT messaging platform and streaming database.

05/13/2026

🌐 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱 𝗗𝗲𝘃𝗶𝗰𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: 𝟱𝟬+ 𝗜𝗼𝗧 𝗛𝘂𝗯𝘀 ➔ 𝟭 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗣𝗹𝗮𝗻𝗲.

Managing a fleet of 10 million devices is a mission-critical challenge. A global tech leader was struggling with the complexity of 50+ cloud IoT hub instances, scalability ceilings, and the lack of reliability guarantees for critical patches.

The solution? 𝗘𝗠𝗤𝗫 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗼𝗻 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀.

𝗧𝗵𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝘁𝗵𝗶𝘀 𝗦𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗠𝗤𝗧𝗧 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲:

- 𝗠𝗮𝘀𝘀𝗶𝘃𝗲 𝗦𝗰𝗮𝗹𝗲: Seamlessly handling 10 million concurrent connections with sub-second latency.
- 𝗚𝘂𝗮𝗿𝗮𝗻𝘁𝗲𝗲𝗱 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆: Exactly-once (QoS 2) delivery for security patches, eliminating custom retry logic.
- 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗖𝗼𝗻𝘀𝗼𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻: Replaced fragmented cloud hubs with a single, Kubernetes-native backbone.
- 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀: 128GB of daily data throughput streamed directly into Kafka for real-time analytics.

By moving from usage-based cloud models to a predictable, high-performance architecture, this manufacturer slashed TCO and achieved 99.99% uptime.

📖 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗰𝗮𝘀𝗲 𝘀𝘁𝘂𝗱𝘆: https://buff.ly/bFYABhI

05/12/2026

𝗦𝘁𝗼𝗽 𝘀𝘁𝗿𝘂𝗴𝗴𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗳𝗿𝗮𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗶𝗻𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗱𝗮𝘁𝗮.

In the world of AI and IIoT, visibility and reliability are everything. Without a structured approach, scaling your infrastructure often leads to "data chaos."

In our upcoming 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗼𝗻 𝗠𝗮𝘆 𝟭𝟵, Ruiz and Dyachkov will show you how 𝗘𝗠𝗤𝗫 𝟲.𝟮 solves these challenges:

- 𝗙𝗼𝗿 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘀: Learn how to implement Unified Namespace (UNS) with ease.
- 𝗙𝗼𝗿 𝗔𝗜/𝗠𝗟 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀: Discover how to coordinate real-time data flows for AI agents.
- 𝗙𝗼𝗿 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀: Master schema enforcement to maintain data integrity at scale.

Don't just connect devices — coordinate your entire system.

🗓️ May 19, 2026
🕒 10 AM PT | 1 PM ET | 6 PM BST
👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: https://buff.ly/qVS6F79

05/07/2026

𝗠𝗤𝗧𝗧 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗶𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗮 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻 𝗰𝗵𝗲𝗰𝗸𝗯𝗼𝘅; 𝗶𝘁’𝘀 𝗮 𝗺𝘂𝗹𝘁𝗶-𝗹𝗮𝘆𝗲𝗿 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲.

For scale-up IoT platforms, the real challenge isn't just authenticating a device, but ensuring its identity matches its token and its permissions align with enterprise policy.

In our latest guide, we dive into how 𝗘𝗠𝗤𝗫 uses JWT claims to automate:

✅ 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁: Stop Client ID spoofing by matching IDs to nested JWT claims.
✅ 𝗦𝗰𝗼𝗽𝗲 𝗠𝗮𝗽𝗽𝗶𝗻𝗴: Automatically turn OAuth/ADFS scopes into topic-level ACLs.
✅ 𝗭𝗲𝗿𝗼-𝗖𝗼𝗱𝗲 𝗘𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁: Standardize security via native expressions, no custom plugins required.

Bridge the gap between your IAM standards and your MQTT infrastructure.

📖 𝗙𝘂𝗹𝗹 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝗲𝗽 𝗗𝗶𝘃𝗲: https://buff.ly/Xo9Maus

05/05/2026

𝗬𝗼𝘂𝗿 𝗳𝗮𝗰𝘁𝗼𝗿𝘆 𝗳𝗹𝗼𝗼𝗿 𝘀𝗽𝗲𝗮𝗸𝘀 𝟭𝟬𝟬+ 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀. 𝗖𝗮𝗻 𝘆𝗼𝘂𝗿 𝗜𝗧 𝘀𝘆𝘀𝘁𝗲𝗺 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲𝗺?

𝗘𝗠𝗤𝗫 𝗡𝗲𝘂𝗿𝗼𝗻 is the lightweight (

04/30/2026

𝗪𝗵𝗮𝘁 𝗶𝗳 𝘆𝗼𝘂𝗿 𝗜𝗼𝗧 𝗳𝗹𝗲𝗲𝘁 𝗰𝗼𝘂𝗹𝗱 𝗺𝗮𝗻𝗮𝗴𝗲 𝗶𝘁𝘀𝗲𝗹𝗳?

The traditional "Reactive" model of IoT, where devices send data and humans respond to alerts, is hitting a bottleneck. As we move into the era of Physical AI, the architecture must shift from centralized command-to-control toward Lateral Coordination.

In our latest deep-dive, we explore why assigning 𝗼𝗻𝗲 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝗽𝗲𝗿 𝗱𝗲𝘃𝗶𝗰𝗲 is the future of resilient IoT:

- 𝗙𝗿𝗼𝗺 𝗦𝘁𝗮𝘁𝗶𝗰 𝗥𝘂𝗹𝗲𝘀 𝘁𝗼 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴: Agents deep-dive into a specific device's history and context, distinguishing between a simple sensor drift and an imminent compressor failure.
- 𝗕𝗿𝗼𝗸𝗲𝗿 𝗮𝘀 𝘁𝗵𝗲 𝗖𝗼𝗼𝗿𝗱𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗙𝗮𝗯𝗿𝗶𝗰: Instead of building complex orchestrators, we use MQTT primitives (Retained Messages, LWT, A2A Registry) to handle agent discovery and state persistence.
- 𝗦𝗲𝗹𝗳-𝗖𝗼𝗼𝗿𝗱𝗶𝗻𝗮𝘁𝗶𝗻𝗴 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀: Watch how a predictive maintenance task moves from a device agent to a diagnostics agent and then to a planner, all without a central dispatcher polling for status.

With the 𝗔𝟮𝗔 𝗔𝗴𝗲𝗻𝘁 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆 𝗶𝗻 𝗘𝗠𝗤𝗫 𝟲.𝟮, the broker is no longer just a message bus; it’s the runtime for autonomous, fault-tolerant agent ecosystems.

📖 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗯𝗿𝗲𝗮𝗸𝗱𝗼𝘄𝗻: https://buff.ly/uZjug1W

04/29/2026

𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝘃𝘀. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲: 𝗧𝗵𝗲 𝗴𝗮𝗽 𝗶𝘀 𝗮𝘁 𝘁𝗵𝗲 𝗲𝗱𝗴𝗲.

OT data usually leaves the factory as fragmented registers. By the time it reaches the cloud, the cost of cleaning it often outweighs its value.

With 𝗘𝗠𝗤𝗫 𝗡𝗲𝘂𝗿𝗼𝗻, you can now standardize, filter, and enrich data at the source through a high-performance SQL stream processing engine.

- 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗙𝗶𝗹𝘁𝗲𝗿𝗶𝗻𝗴: Use Lag() functions for Deadband control, reducing bandwidth by up to 80%.
- 𝗗𝗲𝗲𝗽 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Convert "Machine Language" (Hex, bitwise, split registers) into "Business Language" at the source.
- 𝗧𝗶𝗺𝗲-𝗦𝗲𝗿𝗶𝗲𝘀 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻: Calculate OEE and statistical indicators via Tumbling Windows before data leaves the factory.
- 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗘𝗻𝗿𝗶𝗰𝗵𝗺𝗲𝗻𝘁: Join real-time streams with static metadata to build a Unified Namespace (UNS).
- 𝗘𝗱𝗴𝗲 𝗔𝗜 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲: Run custom Python/Go algorithms for millisecond-level anomaly detection.

By transforming raw telemetry into contextualized datasets at the edge, you don’t just save on cloud costs; you build a solid foundation for Real-Time Intelligence.

📖 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲: https://buff.ly/l713phM

04/28/2026

𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰-𝗚𝗿𝗮𝗱𝗲 𝗗𝗮𝘁𝗮 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆: 𝗛𝗼𝘄 𝗧𝗥𝗢𝗣𝗢𝗦 𝗦𝗰𝗮𝗹𝗲𝘀 𝗔𝗶𝗿 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗘𝗠𝗤𝗫

Distributed sensor networks are the backbone of modern environmental science, but maintaining data consistency across private households and remote locations is a massive technical challenge.

The 𝗟𝗲𝗶𝗯𝗻𝗶𝘇 𝗜𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗲 𝗳𝗼𝗿 𝗧𝗿𝗼𝗽𝗼𝘀𝗽𝗵𝗲𝗿𝗶𝗰 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 (𝗧𝗥𝗢𝗣𝗢𝗦), a key partner in the EU-funded EDIAQI project, needed a resilient architecture to collect continuous atmospheric data for long-term analysis.

𝗧𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻? 𝗔 𝗺𝘂𝗹𝘁𝗶-𝗹𝗮𝘆𝗲𝗿𝗲𝗱 𝗠𝗤𝗧𝗧 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗯𝘆 𝗘𝗠𝗤𝗫:

- 𝗛𝗶𝗴𝗵 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: A dual-node EMQX cluster behind a load balancer ensures 24/7 synchronized data streams.
- 𝗚𝗲𝗼-𝗥𝗲𝗱𝘂𝗻𝗱𝗮𝗻𝗰𝘆: Leveraging Bridge Mode to synchronize data across physically separate locations, crucial for decade-long research projects like ACTRIS.
- 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Integrated with TimescaleDB and Grafana, the team can now identify sensor anomalies during collection, drastically reducing manual data cleaning.
- 𝗡𝗼𝗻-𝗜𝗻𝘁𝗿𝘂𝘀𝗶𝘃𝗲 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Using MQTT as a lightweight protocol allows stable, remote monitoring in private environments without on-site maintenance.

By standardizing on EMQX, TROPOS has moved from simple data collection to a professionalized, scalable operational platform for atmospheric science.

📖 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝘆: https://buff.ly/xz4AsAH

04/27/2026

𝗠𝗤𝗧𝗧 𝗶𝘀 𝗲𝘃𝗼𝗹𝘃𝗶𝗻𝗴. 𝗔𝗿𝗲 𝘆𝗼𝘂𝗿 𝗔𝗜 𝗮𝗻𝗱 𝗜𝗼𝗧 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗿𝗲𝗮𝗱𝘆?

As systems become more distributed, basic messaging isn't enough. We’re excited to introduce 𝗘𝗠𝗤𝗫 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝟲.𝟮, designed for real-time coordination and governed communication.

𝗝𝗼𝗶𝗻 𝘂𝘀 𝗼𝗻 𝗠𝗮𝘆 𝟭𝟵 𝗳𝗼𝗿 𝗮 𝗹𝗶𝘃𝗲 𝗱𝗲𝗲𝗽 𝗱𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲 𝗻𝗲𝘄 𝗲𝗿𝗮 𝗼𝗳 𝗠𝗤𝗧𝗧:

✅ 𝗔𝗴𝗲𝗻𝘁 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆: How AI agents find and interact in distributed environments.
✅ 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: Enforcing topic structures and schemas for higher data quality.
✅ 𝗦𝘆𝘀𝘁𝗲𝗺 𝗖𝗼𝗼𝗿𝗱𝗶𝗻𝗮𝘁𝗶𝗼𝗻: Orchestrating flows between devices, apps, and AI services.

Whether you're building a Unified Namespace (UNS) or scaling AI-enabled industrial systems, see how EMQX 6.2 fits into your modern architecture.

👉 𝗦𝗮𝘃𝗲 𝘆𝗼𝘂𝗿 𝘀𝗲𝗮𝘁: https://buff.ly/lhP2bJB

04/23/2026

𝗦𝗰𝗮𝗹𝗲 𝘆𝗼𝘂𝗿 𝗜𝗼𝗧 𝗗𝗮𝘁𝗮 𝗳𝗿𝗼𝗺 𝗣𝗿𝗼𝘁𝗼𝘁𝘆𝗽𝗲 𝘁𝗼 𝗠𝗶𝗹𝗹𝗶𝗼𝗻𝘀 𝗼𝗳 𝗗𝗲𝘃𝗶𝗰𝗲𝘀 𝘄𝗶𝘁𝗵 𝗘𝗠𝗤𝗫 𝗧𝗮𝗯𝗹𝗲𝘀.

Most databases force a painful migration when your device fleet outgrows a single node. 𝗘𝗠𝗤𝗫 𝗧𝗮𝗯𝗹𝗲𝘀 (powered by GreptimeDB) changes that with a "no-ceiling" distributed architecture.

𝗛𝗼𝘄 𝗘𝗠𝗤𝗫 𝗧𝗮𝗯𝗹𝗲𝘀 𝗺𝗮𝗸𝗲𝘀 𝗶𝘁 𝘄𝗶𝘁𝗵 𝗚𝗿𝗲𝗽𝘁𝗶𝗺𝗲𝗗𝗕:

- 𝗦𝘁𝗮𝘁𝗲𝗹𝗲𝘀𝘀 𝗜𝗻𝗴𝗲𝘀𝘁𝗶𝗼𝗻: Add write capacity instantly as your MQTT traffic grows.
- 𝗥𝗲𝗴𝗶𝗼𝗻-𝗕𝗮𝘀𝗲𝗱 𝗘𝗹𝗮𝘀𝘁𝗶𝗰𝗶𝘁𝘆: Data is partitioned into "Regions" that migrate across nodes as simple metadata operations. No slow bulk data copying.
- 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗔𝗴𝗻𝗼𝘀𝘁𝗶𝗰: Move from Standalone to a Distributed Cluster without changing a single line of your SQL, pipeline, or Grafana dashboards.

📖 𝗥𝗲𝗮𝗱 𝗽𝗮𝗿𝘁 𝟯 𝗼𝗳 𝗼𝘂𝗿 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝘀𝗲𝗿𝗶𝗲𝘀: https://buff.ly/Xi6MgzY

04/22/2026

𝗕𝗿𝗶𝗱𝗴𝗲 𝘁𝗵𝗲 𝗢𝗧-𝗜𝗧 𝗚𝗮𝗽 𝗶𝗻 𝟭𝟱 𝗠𝗶𝗻𝘂𝘁𝗲𝘀: 𝗘𝗠𝗤𝗫 𝗡𝗲𝘂𝗿𝗼𝗻 𝗺𝗲𝗲𝘁𝘀 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰

The biggest hurdle in Industry 4.0 isn't a lack of data; it's "incomprehensible" data trapped in fragmented PLC protocols.

We’ve just released a step-by-step guide on building a seamless data pipeline from the factory floor to the cloud using 𝗘𝗠𝗤𝗫 𝗡𝗲𝘂𝗿𝗼𝗻 𝗮𝗻𝗱 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰.

𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗰𝗼𝗺𝗯𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗮 𝗴𝗮𝗺𝗲-𝗰𝗵𝗮𝗻𝗴𝗲𝗿 𝗳𝗼𝗿 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗜𝗼𝗧:

- 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 "𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗼𝗿": EMQX Neuron converts 100+ industrial protocols (OPC UA, Modbus, Siemens S7) into standard Kafka streams at the edge.
- 𝗘𝗱𝗴𝗲 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲: Clean and aggregate data via a built-in SQL engine before it leaves the factory, reducing cloud costs by up to 90%.
- 𝗦𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀 𝗦𝗰𝗮𝗹𝗲: Microsoft Fabric’s Eventstream provides native Kafka compatibility and millisecond-level ingestion without managing complex clusters.
- 𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: Move from raw sensor data to Power BI dashboards and predictive AI models within a single, unified OneLake environment.

📖 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗙𝘂𝗹𝗹 𝟭𝟱-𝗠𝗶𝗻𝘂𝘁𝗲 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹: https://buff.ly/XjIXFKu

04/21/2026

𝗪𝗲'𝗿𝗲 𝗹𝗶𝘃𝗲 𝗮𝘁 𝗛𝗮𝗻𝗻𝗼𝘃𝗲𝗿 𝗠𝗲𝘀𝘀𝗲 𝟮𝟬𝟮𝟲!

𝗛𝗮𝗹𝗹 𝟭𝟱, 𝗦𝘁𝗮𝗻𝗱 𝗘𝟮𝟱. And something is happening on our factory floor that you need to see in person.

We brought 𝗿𝗼𝗯𝗼𝘁𝘀. We brought 𝗠𝗤𝗧𝗧. We brought 𝗮 𝗱𝗲𝗺𝗼 𝘁𝗵𝗮𝘁 𝗱𝗼𝗲𝘀𝗻'𝘁 𝘂𝘀𝗲 𝗮 𝘀𝗶𝗻𝗴𝗹𝗲 𝘀𝗹𝗶𝗱𝗲.

If you're walking the show this week, stop by. The team is here all five days and would love to show you 𝘄𝗵𝗮𝘁 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗜 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗯𝘂𝗶𝗹𝘁 𝗿𝗶𝗴𝗵𝘁.

𝗖𝘂𝗿𝗶𝗼𝘂𝘀? 𝗦𝘁𝗮𝗿𝘁 𝗵𝗲𝗿𝗲: https://buff.ly/KfsxmdW

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