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We built Gravio to Enable you with IoT and AI Capabilities at the Edge. No-Code/Low-Code.

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Global brands are using Gravio

Top 3 reasons why our customers chose Gravio
Edge Computing - Benefit from being on-premise, speed and security.

Hardware Sensors and Software Sensors in One - Computer Vision and IoT in a single platform.
Extremely Easy to Use - No programming skills required to build Gravio applications.
What is Gravio?
Intuitive Visual Interface

Gravio is an easy-to-use software platform that runs on Windows, macOS or Linux. You can connect to various inputs and outputs, including some bundled IoT sensors, computer vision/AI cameras and MQTT or HTTP APIs. Gravio is very easy to use without software programming knowledge.


Unlike other platforms, Gravio does not attempt to establish new standards. Instead we rely on industry standards such as Zigbee, ONVIF, MQTT, Rest APIs, Tensorflow and many more.

Gravio supports hardware sensors as well as software sensors (camera systems + computer vision AI).

Rapid Integration

Gravio enables you to create micro-programs that run at the edge, called "Actions". With Actions you can connect various inputs, such as sensor or camera inputs with various easy-to-configure output channels such as APIs, notification systems or various devices at the edge.

Edge Computing

Edge computing can improve efficiency, resiliency and security by distributing the system more from a centralized system. Furthermore, transferring sensitive data such as CCTV images to the cloud are problematic from the data protection point of view. However if the data is processed on site at the Edge of a network, such issues can be avoided.

How does Gravio look like?
Gravio unlocks the power of connected technologies by connecting sensors, input devices, cameras and APIs within a space, then continuously gather and share their information - enabling new ways to interact with, learn from and enhance a physical space.

Gravio is a product of Asteria - the Japanese market leader of application integration software - who believes in the power of connectivity, and the vast potential for connected spaces.

Gravio is a partner of the Kinetic Edge Alliance, which is an alliance of industry-leading companies collaborating to make designing, deploying and operating edge computing easy. More information on https://www.vapor.io/partners/kinetic-edge-alliance/
The Kinetic Edge Alliance | Vapor IO  https://www.vapor.io

What Customers and Partners say
Find more feedback on G2
What is Edge Computing?
Rather than connecting and transferring all data to a cloud system, majority of the data will be processed locally at the edge of the network, where it is generated. This distributed approach makes systems faster, more resilient and keeps the data safer, because it does not necessarily need to connect to the Internet. A great example for Edge computing are connected, smart or even self-driving cars. They will do much of the computation at the edge of the network, i.e. in the car. While only information that needs to be shared for example with an app will be sent to the central cloud system to be processed.

Cloud Computing

Edge Computing

The Edge servers can be connected efficiently between each other as well as to a cloud system.
Example: Image Processing in the Edge

Edge Computing leverages the power of distributed systems. It allows for more efficiency, resilience and security. Gravio is built on the premise that in the future, systems will process data on the edge of the network rather than in a centralised cloud. For example, Edge Servers will process local image data, extract the necessary information using Artificial Intelligence and discard the image before passing the extracted information on via the internet.

How is Gravio used?
Gravio can be used in many different contexts thanks to its versatility and flexibility. Whatever business you are in, the better you leverage the data, the more successful your organisation will be.

Here are a few examples of how that could look:
Optimise Footfall
Optimise Footfall
Smart Shops and Restaurants

Brick and mortar shops as well as restaurants can benefit greatly from data generated such as footfall, occupancy rates, percentage of people coming into the venue, whereabouts they dwell, what they are buying and how they behave. Identifying trends such as decreasing relative footfall early can be crucial for a business, to its tactics and ultimate survival. Gravio helps you up-smart your existing infrastructure easily and turn your business into a "smart location".

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Gather Data
Gather Data
Smart Cities

Urban dwellings are now collecting enormous amounts of data. To optimise the efficiency of a city, it is crucial to track and analyse flows of people, traffic and goods to make informed decisions. A distributed system such as Gravio can gather this information in a decentralised fashion and pass on any pre-processed information efficiently to a central instance for further analysis. Gravio can be deployed easily and scaled up efficiently.

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Analyse and Measure Improvements
Analyse and Measure Improvements
Optimisation of Business Processes

Business processes have become much more sophisticated and therefore complex in the past few decades. Especially connectivity, monitoring, sensor deployment and use of “intelligent systems” have started entering the industrial production process, most notably with “Industry 4.0” initiatives. With Gravio, information can be captured at large scale in real-time to be processed further or to be analysed for optimisation.

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Observe and Alert
Observe and Alert
Predictive Maintenance

Even a few minutes of outage in a production line can mean losses of thousands of dollars. Connected devices and sensors are increasingly used to predict breakdowns before they happen, so replacement can be put in place in time or precautions can be taken. Gravio, alongside with its data processing and Artificial Intelligence capabilities is able to provide a reliable system that can minimise plant or production outage by predicting outages and alerting the right stakeholders timely.

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