Who we are

We deliver analytical insights, leverage machine complex data, and empower end-users with business intelligence.

Chosing an edge computing platform

Choosing an Edge Computing Platform

Does 25ms sound unreasonable to process Terabytes of data? Well it is in today’s IoT world – to collect gigantic amounts of data, process and analyze it, and generate snappy dashboards in just 25ms.

Leaders across industries are emphasizing that data absolutely has no value if it cannot be processed and transferred to a decision maker quickly enough for him or her to act quickly enough. Today, it’s impossible to accept even a minute’s delay.

Edge computing is propelling those huge expectations. And it ought to be.

Smarter cities through iot analytics

For the first time in history, MORE PEOPLE LIVE WITHIN CITIES than outside them. This huge influx of people means that cities have to be able to find ways to quickly provide services to larger numbers of people, rapidly uncover and analyze pain points in providing these services, and plan ahead to accommodate the continuing migration. In particular, more people translates to more cars on the road.

IOT for farming

When you think of life on the farm, a life of waking up before the rooster crows, then heading out to the fields for the day to seed, plow, fertilize and reap in the hot sun before going home for the night and starting over the next day usually come to mind.

Edge analytics in glassbeam

So you heard me TALK ABOUT edge computing. Now lets look at edge analytics. In other words, dynamically created business rules implemented at run time? Hmmm, great idea, but difficult to implement. Even more difficult if you further simplify the generation of such rules through an intuitive drag and drop UI. Analytics is another name for early action and Rules are key to making that happen. Rules allow us to:

Glassbeam edge computing – a primer

As the Internet of Things inevitable starts coming into it’s own, the origin of data has evolved from people to machines to “things”. Technologies emerged from leaders like Google and Facebook to enable analyzing tons of data in massive data farms deployed in the cloud. All that is well and good, but the approach itself needed moving this “ton” of data to a central location, partition it across large number of nodes so that analysis could be parallelized. Imagine, Netflix has over 1,000 nodes in their cluster. Hmmmm, doable, but at some point the laws of physics start to interfere.

Glassbeam studio architecture

GLASSBEAM STUDIO is a one of a kind software which helps in data transformation and preparation, visualizing data, deployment and much more. The Glassbeam Studio technology is modeled on a client-server architecture with functionalities balanced neatly between the client and the server. This software is architected to offer an infinitely scalable, seamlessly, and functionally compelling way to transform even the most complex machine data into valuable business insights.

Metadata extraction

Introducing glassbeam studio

I am delighted to announce the release of Glassbeam Studio – the industry’s first Data Transformation and Preparation tool for complex machine data.

According to Gartner, by 2018, data discovery and data management evolution will drive most organizations to augment centralized architectures with decentralized approaches. Most business users and analysts will have access to self-service tools to prepare data for analysis.

IOT in our daily lives

I met an old friend after quite a white this past weekend. I barely uttered the word ‘IoT’ while updating him on my career, and he immediately began gushing at what the industry had done for him.

He mentioned how, on the golf course last weekend, he he sliced (yet another!) drive into the woods, and an app connected to his driver reminding him how to straighten his wrist to fix his swing. His wife came home last weekend with a smart flower pot that now alerts him on when it needs to be watered and fed.

New iot applications take benefits to a new level

CB INSIGHTS, which offers range of consulting, research and database services to the venture community, recently published a series of articles that demonstrates the continued growth and accelerating adoption of IoT Applications.

One ARTICLE traces IoT funding, noting there has been $500 million in investments in private IoT companies in four of the last six quarters.

Semiotic parsing language – the language for machine data analytics

The Internet of Things (IoT), an ever-growing number of connected devices, generates vast amounts of data, called “Machine Data”, complex in variety, volume and velocity. Machine data is information about the device, like its configuration, status, performance, usage and more. Manufacturers across data-intensive industries – such as storage, wireless, networking and medical devices – are struggling to make sense of all this data. Analyzing machine data can help organizations with reactive diagnostic activity, predictive problem identification, and business intelligence.

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