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predixionsoftware.com

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Stage

Acquired | Acquired

Total Raised

$35.83M

About Predixion Software

Predixion Software has developed Predixion Insight, a cloud-based analytics platform that provides real-time, predictive analytics at the decision point in order to improve outcomes. Predixion specializes in the "Last Mile of Analytics"- that is getting the power of predictive insights to the front lines where decisions are made – whether that is an application, a BI dashboard, a machine or a device.

Predixion Software Headquarter Location

15 Enterprise Road Suite 300

Aliso Viejo, California, 92656,

United States

949-373-4900

Latest Predixion Software News

Consumer IoT is the shiny toy, real money and opportunity is in the enterprise space: Varun Arora, Greenwave

Jan 4, 2017

Greenwave has not yet explored Smart-City or Corporate IoT projects, which Arora believes, the company is now ready to tap Talking about the 7 year old IoT company, Varun Arora, Vice President of Business Development, Greenwave Systems says that it is focusing on helping service providers and MSOs (cable, broadband-internet companies, utility companies and telecommunication) deliver new revenue streams through IoT and other end to end services. He says that there is a lot going on in the IoT sphere and when it comes to churning big-data that comes out of IoT, it is beneficial to have edge-analytics, which is also one of the reasons why Greenwave made the recent acquisition of predictive analytics company Predixion Software. Excerpts:  Techseen: There have been speculations that you have taken Goldman Sachs on board for a possible IPO. is it true or just rumors? Arora: Goldman Sachs is advising us on our funding strategy currently. Whether we decide to take the company public or we decide to take another round of funding, the timing is something that we are not ready to announce just yet, but we are looking at all kinds of possibilities. Not too long ago, December of 2015 last year we closed a fairly large round of $60 million in funding and have been able to keep the company profitable which is rare in this space. A lot of companies raise a lot of cash just to burn through it very quickly, that is not what we want to do. We do have a bunch of cash and we are using it very carefully for in-organic growth, we made an acquisition recently in the analytics space. If we do raise more money or make the company public it has to be really driven by what we need to use the money for and that is an ongoing discussion. Techseen: Talking about acquisitions, you acquired a predictive analytics company Predixion for enhancing Axon, your IoT platform. Why does Axon need an enhancement, what kind of enhancement were you looking for? Arora: When we say enhancement, what we really mean is the need of the customer. If you look at the IoT space, analytics is super-important and we did not have an analytics piece. We could gather data but to actually present that in a meaningful form to the customer, was not an existing strength of Greenwave. This is where you can say it enhances the Axon Platform, but what it also does is present different kinds of business opportunities. This is not just your standard analytics company, this is a company that specializes in edge-analytics. Which is really about being at the network edge than bringing all the data back home. The problem with regular analytics is that you end up bringing so much data, that storing and managing it becomes expensive, responding to it becomes difficult. The real value of data is the time and point it has originated from. That is one area where Predixion plays a huge role, because they have perfected the science of low-power edge-analytics. It helps us to work with various hardware companies and organizations where there is a lot of data but low bandwidth; where you cannot upload a lot, that is were, working locally comes in handy. Techseen: You talk about IoT and machine to machine communication, what are the major challenges that you are facing in the market when it comes to delivering the concept and technology? Arora: There are a bunch of different technologies in the market, one of the confusions in the market is about what technology to adopt. You could go with NB IoT, with LORA, FOX, etc. if you look at who is deploying what, typically the service providers should deploy the TCP compliance standard, especially the telecommunication, because they have the telco infrastructure and they have to follow the ideal standard. If you look at a non-telco company, they consider using LORA. A cable company would ideally use LORA, an enterprise would use LORA or FOX though the investment is not too much. Also Read:  What's in stock for Big Data in 2017; Tableau predicts The competing standards creates some confusion, the other piece that creates concern among them is the barriers. According to studies 60% of enterprise CIOs say that bringing data from different sources is become a big problem, and that is why edge-analytics is so important, it helps to bring together a lot-lesser. Similarly 80% say that the volume of data is overwhelming, and 80% think that people do not have the right skills or understanding. We do know what we are doing and where the industry’s graph is moving, since our CTO as well as our Chief Scientist who co-founded the world’s first IoT company. With all this knowledge, it gives us an edge in the market and customers tend to value that. Techseen: Is the future of Internet of Things Industrial IoT? Are real world applications revolving around IIoT rather than consumer technology? Arora: I think that consumer IoT is the shiny toy, for example at home I have an Amazon Echo connected with the lighting and I can just say Alexa turn on the lamp and control the lighting, and I am now looking at having AC control and a bunch of other stuff. But that is fun, it does not significantly change my life, rather a cool thing to play with. The real money and the real opportunity on the IoT side are definitely in the enterprise space. Which again speaks to another reason for us to acquire Predixion, because it gets us into a space that we have not played before. We have done something like smart energy but we have not done anything like a smart-city project. We haven’t really done corporate IoT projects, I think that is where the money really is. Techseen: Are enterprise IoT M2M solutions leaning more towards infrastructural connectivity? Arora: I would not say connectivity, let me put it this way; I think it was IDC that estimated that IoT spending would be $1.7 trillion by 2020 and devices, connectivity and services would make up two-thirds of that. Connectivity is certainly where the telecommunications companies have a big role to play since they know how to manage connectivity. When it comes to enterprises, its not about putting the sensors but managing those, with the right to deploy, power management, device management; all of which the telecom companies have figured out. I think there is a role in the connectivity side for the telecom companies but for the enterprises, its really more on services and systems, that’s where the spending is going. IDG found that 70% of organizations are planning projects and 30% have already started targeting projects. Also Read:  Telit and Intel partner to deliver 'joint architecture' IIoT Techseen: One of your Data Scientist and senior professional, Jim Hunter, talked about IoY rather than IoT. What are your views on IoY? Arora: He tends to take a different view, a detached kind of view. He says that IoT has always been around, he takes this from a consumer perspective not an enterprise angle. He said the internet is always been about things, but when you talk about consumer IoT, its really about ‘you’; your preferences, what do you like, how do make your life convenient and the things have always been around that. Its about learning the consumers’ pattern and needs. An example: What the government is doing in Singapore is also interesting, it has rolled out a pilot project for elderly management, in one of the districts. Singapore’s population has drained fairly rapidly, we are not replacing at the rate we need to replace and because of that the population is aging. That puts all kinds of pressure on healthcare and hospitals. One of the things that we want to do is to monitor the elderly in a non-invasive manner. The pilot project that I referred to comes in here. We have been putting all kind of sensors in an elderly home, on a voluntary basis, these sensors include sensors on doors for opening and closing, sensors on beds that detect how long a person is on it, sensors on flushes, that detect how many times a person flushes in the day, movement sensors that track how much a person moves in the day. And with this data, the government is using predictive analytics to see if there is a change in behavior to create an alert. This is an example of IoY, its about managing health and not just about the technology. Techseen: There is a lot of data that comes out of IoT, what does Greenwave do with all the big data? Arora: Gartner says that by 2020, 40% of data generated on the internet will be from sensors. If you look at the number of sensors themselves its huge. Cisco believes that there will be 50 billion by 2020, McKinsey says 20-30 billion and Gartner says 20.8 billion. So what we are looking at is 20-50 billion devices generating 40% of data. As there is too much of data, it becomes difficult because there is way to much to analyze. What drives a lot of this is organizational immaturity and I don’t mean immaturity from a childish sense but from a skill and knowledge and what to do with it perspective. In terms of what data will be meaningful. You don’t want to take a chance on not collecting something that may come in handy. As a result you end up with huge storage problems and huge analysis problem, even the data scientists don’t know what to do with the data. That also speaks about why edge-analytics is so critical. If you can do it at the edge, you only need to relay what you need. And drop the rest on the spot. Let’s take another example of Singapore, what the government is doing with elevators is interesting. There are 24,000 public elevators in housings in Singapore. If you think about public housing, 35% of Singapore lives in public housing, which is quality housing subsidized and managed by the government. The government has started putting in sensors that monitor those elevators. It checks and does predictive analysis for maintenance for those elevators. You don’t have to wait for a resident to call and complain, they already know. Now they are trying to go beyond that and say don’t send all the data back, try and determine predictively if an elevator is about to break down and send the maintenance before it happens, which is better than monitoring all the 24,000. So doing analytics on the edge makes a lot more sense. Also Read:  Traction Gap: A new startup-focused framework IP from Wildcat Venture Partners Techseen: What is the need of the hour when it comes to IoT solutions? Arora: The data basically says that the key challenge today is that there is a need to bring together data from different sources and this data is sometimes is not clean, it can have different variations of the same answer or different variations of the same variables and there is a need to clean them up. So there are Patnis of the world that are just focusing on cleaning up and managing Big-Data and I think that is a huge area of work from an enterprise perspective. From a consumer perspective, it’s a question of too many technologies or standards and confusion and bewilderment for those who are early adopters. That is an area where we try and make a difference as we abstract away all the technology, so if you think about it from a technology perspective you have all kinds of channels, what should a consumer buy? If we look at looking at this from our service providers’ perspective, it leaves them scratching their heads thinking what should we do? That is also where we abstract all the technology away and enable the different technologies to talk to each other. Whether it is applying different communication channels like WiFi or Bluetooth or ZigBee or Z-wave, what matters is that it is a light that needs to be switched on.

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Expert Collections containing Predixion Software

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Predixion Software is included in 6 Expert Collections, including IIOT Landscape.

I

IIOT Landscape

498 items

Companies in the industrial internet of things space, including sensor analytics platforms, edge computing, asset tracking, and more.

E

Enterprise SaaS

2,452 items

Software-as-a-service (SaaS) – internet based software offered as a subscription – continues to become the de facto standard for software distribution and consumption. Enterprise SaaS continues to show particular promise, emerging as one of the most well-funded categories. Startu

I

Internet of Things ( IoT )

3,149 items

b

big data

1,068 items

A

Artificial Intelligence

7,340 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.

I

Industrial Predictive Analytics

53 items

Software that helps operators predict maintenance events, downtime, and energy usage.

Predixion Software Patents

Predixion Software has filed 1 patent.

patents chart

Application Date

Grant Date

Title

Related Topics

Status

8/13/2013

Actuarial science, Data mining, Machine learning, Business intelligence, Data management

Application

Application Date

8/13/2013

Grant Date

Title

Related Topics

Actuarial science, Data mining, Machine learning, Business intelligence, Data management

Status

Application

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