Every generation there is a company that allows technology to catch up to idea demand. Fortune 500 companies are overwhelmingly using HiveMQ as the backbone for data and device connectivity. Mercedes Benz, Sirius XM, BMW, ZF, Moen, and more use them to power business-critical use cases in connected cars, logistics, connected products
Almost every company currently faces data connectivity challenges. There are data silos, networks are unreliable, they can't get data in real-time, the data comes from varied sources, and the whole system is difficult to unify. HiveMQ is the central nervous system for the Internet of Things, giving companies a way to overcome all of these obstacles with a platform built on MQTT so they can do more with their data. MQTT stands for Message Queuing Telemetry Transport.
"MQTT is a solid choice for a variety of reasons - efficient and easy to implement, requires low bandwidth and power (which is good when sensors and smart devices at the edge face latency issues). In many ways, we could see IoT and AI elements coming together (artificial intelligence can even be used for intrusion detection with cybersecurity). As things advance, we might see connections to machine learning and other emerging technology (augmented reality, HealthTech, infrastructure monitoring, homeland defense, and beyond)" said IOT Community board member and expert Ian Gertler.
Businesses want to focus on their core value - whether it be a connected car platform, a drone that carries medical supplies, or a connected dishwasher. They don't have the time or the expertise to worry about the data moving from point A to point B. HiveMQ powers dozens of use cases with the scalable, secure, and reliable delivery of data. So, the BMW car door opens in sub one second instead of 30, the drone gets the medical sample to the hospital 75% faster, and the dishwasher tells the owner when the detergent is empty.
Mercedes Benz achieved 100% uptime for a business critical manufacturing diagnostic system, rolled out to 24 global factories. Flo by Moen Smart Water Detectors catches leaks as small as one drop per minute, preventing water leak damage and conserving valuable resources.
And while heading into 2024 you might not have been thinking about MQTT; it will power many of the innovations we see. MQTT is the de facto standard for IoT messaging because it requires minimal resources and is lightweight, can scale to millions of devices, and works well over unreliable networks.
Even with MQTT's inherent benefits, it's just a specification. HiveMQ adds features like zero message loss, consistent communication, zero-downtime upgrades, and a cluster architecture for no single point of failure. Their reason for growth is they don't lose messages, even in the midst of unreliable networks or other real-world challenges. There is zero room for error when it comes to important data. This is where HiveMQ has found a way to thrive and carry MQTT into the mainstream.
The data company accelerating scientific breakthroughs in 2024
In the scientific R&D space, we see scientists increasingly working with software companies like Dotmatics to become AI-ready. Dotmatics offers software that is used by more than 2 million scientists globally from Bristol-Myers Squibb and Merck to research universities like MIT and Oxford. The goal? Accelerating scientific discovery to create a healthier, cleaner, safer world, and they believe that data science meeting science data is the answer.
Scientists today working on life-saving discoveries from cancer research to food scarcity struggle with having their data locked in silos.
As humans work to coalesce the various outputs across instruments, significant data integrity risks are introduced at every stage. And as instrumentation manufacturers update and change formats, labs find that scripts break and require updates, which halts any automated data wrangling or analysis efforts. It's an exceptionally complicated and inefficient process. That's why bringing a single drug to market costs on average around $2.5 billion dollars, takes 10 years, and for every drug that gets approved, ten thousand compounds will fail.
It's why Dotmatics is doing is so intriguing. Dotmatics worked with many of the top ten pharmaceutical companies in the world to develop a new scientific data platform called Dotmatics Luma. Luma can handle both the volume and complexity of data, across lab instruments, and at exponential scale, but perhaps more importantly, it's built to do so in a way that scientists can easily control all on their own. Dotmatics is adding AI functionality with generative AI query-building options and, over time, predictive and adaptive AI that will greatly augment lab testing and decision-making procedures.
The goal is to bring that convoluted and expensive drug discovery process down from billions to millions of dollars and get life saving therapeutics in the hands of patients much faster.