Thought Leaders in Internet of Things: Sridhar Iyengar, CEO of Elemental Machines (Part 4)

Sramana Mitra: What level of adoption are we talking about in LabOps as you call it. What is the pace of adoption in this world?

Sridhar Iyengar: It really depends on the type of company that we’re working with. I mentioned synthetic biology. These companies were very early adopters because of the need of the data. The reason why I highlight this community is, I have a thesis. The more traditional biotech and pharma companies were founded and led by traditional scientists.

The way research was done was very cause-and-effect. You have a hypothesis. You do a bunch of experiments. You get data and understand what happened before you take the next value-added step. There’s nothing wrong with that. However, when you look at the new generation of startups, many of them are founded and run by not necessarily classically-trained scientists but by computer scientists or engineers.

The way these folks approach the same problems can be quite different. It’s very much like a correlation-based approach. I say that because you don’t necessarily need to understand why something works as long as you know how to get it to work repeatedly. I was trained as an engineer in my undergraduate. When you employ machine learning and AI, a lot of that is correlation-based. You can take the next value if you can measure everything and make sure you’re within limits.

The measure-everything aspect is something that’s been embraced by the synthetic biology community early on. That’s my own opinion. In the last two years, we’re seeing widespread adoption by the more traditional biotech and pharma companies because they’re not embracing automation. When you’re building automation systems, the idea is you can run it without being there. Remote monitoring and data from everything becomes much more important. As companies shift to a data-first approach, the need for our products and data collection platform becomes that much more critical. 

Sramana Mitra: Do you have competition in the space or are you the pioneering company?

Sridhar Iyengar: I’d like to say, in one regard, we’re unique. In another regard, there’re a number of companies that we overlap with. One thing that we’re unique in is we have our own hardware. We have cloud-based computing and analytics. Third is we have deep expertise in machine learning.

Our analytical capabilities are quite unique. We are able to take data from various sensors and put a layer of interpretation on top of that. Probably the best example I can give you is, we can look at how machines are running and understand anomalies, events, and usage patterns. How do we characterize the usage and anomalies so that we can do failure prediction?

The fact that we can do hardware, cloud, and data science puts us in a very unique position. A number of companies just do IoT monitoring. That’s table stakes. There are other companies that do the software and analytics piece, but they don’t do the hardware. As long as you can pipe data into their system, they’ll do the visualization and the analytics piece. It’s garbage in, garbage out.

Our core thesis is you’re not collecting data as you should or could. You need to collect more and you do that by using our platform. Many of our customers will have existing software and analytical capabilities. The data that is going into them is limited. We come in and say, “Do you want to put 200 more sensors?” That’s how we create value – widening the pipe of data. We’re quite unique in the fact that we do all three.

This segment is part 4 in the series : Thought Leaders in Internet of Things: Sridhar Iyengar, CEO of Elemental Machines
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