“The world is increasingly getting networked and “connected” with the explosion of Internet of Things.”

Glassbeam Inc. is a Big Data applications company specializing in multi-structured machine data analytics for IT and business users. Glassbeam’s Big Data applications for customer support, product development and sales leverage the company’s breakthrough Semiotic Parsing Language (SPL) that can quickly extract strategic intelligence from complex operational data contained in multi-structured machine data.

Glassbeam’s technology enables customers to parse and mine machine data to make better strategic and operational business decisions. Glassbeam customers and partners include Fortune 500 companies and enterprises across a variety of markets including storage, wireless, networking and medical devices.

What inspired you to launch your business?

I fundamentally believe that machines are more truthful and smarter when reporting on their actual usage and faults, than trying to get the same insights through customer surveys, field reports or industry data. In other words, my core belief is that machines never lie, while information received through any other source gets lot more filtered and altered based on the circumstances.

After I left NetApp in 2005, I spent about four years running a services company, re-affirming my faith in this mission by helping customers, such as NetApp and Hitachi Data Systems mine value out of their machine data from services engagements. In 2009, we launched Glassbeam as a SaaS play, since I always wanted to run a software company with far more impact and higher valuation for all shareholders.

What issue does your core product help solve and how so?

Our core product value lies in converting raw machine log data into actionable information. As a cloud based solution, we can process any format of log data, whether streams or files, and uncover hidden intelligence through applications like Glassbeam Search, Glassbeam Workbench, or Dashboards. Glassbeam Search allows unified search and log management solutions for application and device logs to narrow down and troubleshoot issues in minutes instead of days. Glassbeam Workbench provides the ability to do ad-hoc business intelligence queries in seconds and uncover usage patterns across worldwide installed base of devices and customers. For areas where Search and Workbench is unable to provide out-of-box analytics, Glassbeam platform allows creation of custom dashboards by specific use cases. A recent example of custom set of Dashboards that has been now productized as a new offering is Glassbeam Health Check that allows a product manufacturer to provide value add services to its customers and generate new revenue streams.

What’s the most exciting thing on the horizon for you/your Company?

Glassbeam is riding an incredible wave of opportunity in the Big Data and specifically in the Machine Data analytics market. Our core expertise lies in making sense of complex multi-structured machine log data from complex devices like storage, servers, wireless networks, medical devices etc. Having gained a strong foothold in these select few verticals, the company is looking to go deep into these markets and gain a leadership position in near horizon.

Where do you envision your company in 5 years, 10 years, 20 years?

The world is increasingly getting networked and “connected” with the explosion of Internet of Things. All this implies massive amounts of machine data from sensors, devices, networks, clouds and almost anything that is architected with high technology in mind. If we think we have seen Big Data, what we will see in next 5-10-20 years will be an unprecedented increase in the amount of data generated from all over. All this data will need a platform to collect, assimilate, search and analyze hidden business & operational value in log data. That is our mission at Glassbeam. We want Glassbeam to be the guiding light in the age of “Internet of Things”. In next 5-10 years, we want Glassbeam to be the platform of choice for making sense out of machine log data and help our customers deliver on the promise of actionable intelligence.

How did you come up with your company name?

Good analytics need to be clear, precise, honest and focused with actionable results. These traits form the core of which one should be while delivering analytics to the customers and market. As we went about searching for the right name of our company, which was all about delivering analytics value from “truthful” machine data, it was important for us to embody these virtues and convey them through a simple name. This is where the name Glassbeam was born. Glassbeam, as a name, conveys clarity, focus and precision in terms of what work we do, how we do and who we do it for. When you mine machine data to derive meaningful value for business users, the final output (analytics) has to be presented clearly, precisely and with a distinct focus on making an impact in that business use case. That’s what we do as a living for our leading customers like IBM, Hitachi Data Systems, EMC and many others today.