Mobodexter

Special Update - Our clients like us because we help them save money

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Published on Nov 23, 2017

As promised, in this founding anniversary update we decided to focus on how we help our clients to save money.

Paasmer Edge 1.0 provides three layers of software for the Edge (Devices side). For Paasmer Edge to run they need to high compute hardware like Intel Quad-core or ARM Octo-core.

1) Edge Analytics (EA) - First Layer Data Filter

2) Edge Machine Learning (EML) - Second Layer Data Filter & Intelligence

3) Edge Artificial Intelligence (EAI) - Third Layer Data Filter & Intelligence

When sensors generate data every second, in existing devices like a NEST Thermostat, all the data is moved to their cloud leading network traffic between the device and cloud + Cloud storage space. Let's say the costing of running the cloud for a year is $1 Million per year for the company.

Paasmer Edge Analytics - when applied to the sensor data, would first filter the data. The simple mechanism here is to send only changed data. There is no need to act on temperature data that is not changing. Edge Analytics filter looks at the data and filters it. This reduces the network traffic, data storage, and cloud cost by at least 50%. We cut the cost for our clients from $1 Million to $500,000 at this stage itself.

Here is Paasmer Edge Analytics in action in a client use case:


Paasmer Edge Machine Learning - when this software is configured to handle the above-filtered data from sensors this software add a filter and can trigger actions. In a thermostat scenario, if there is a pattern of thermostat operation once instruct Edge Machine Learning to follow the pattern only. If the device is operated in the pattern then you can avoid further network & storage traffic to the cloud + the device will operate even if there is no connection to the cloud. This is called Intelligence on the device itself. This reduces the cost of operating the cloud by another 50%. We cut the cost for our clients from $500,000 to $250,000 with this software along with Edge Analytics.

Here is Paasmer Edge Machine Learning in action in another client use case:


Paasmer Edge AI - when this software is configured to handle the device data from the sensors more advanced algorithmic actions can be triggered without much interaction with the cloud. You can set a thermostat to operate in the most cost-effective way. The AI system figures out the way without the need for user interaction and this is done on the device itself without the need to connect to the cloud. This software reduces the cost of operation by another 50%. We cut the cost for our clients from $250,000 to $125,000.

Here is Paasmer Edge AI in action in another client use case:


With this three software, we bring our client's yearly operational cost from $1 Million/year to $125,000/year. That's whopping reduction in operating cost.

Paasmer Edge 2.0, due for release in 2018,  is more advanced technology innovation from Mobodexter team that will help to take all the software in one software bundle and each of this software can be run as application software container on the devices allowing our clients to turn on/off based on their need.  This way they get billed for our software based on their run-time making it much more cost-effective than paying for our license cost based on installation.

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