How Robin Purohit of Plans to Make Support Tickets Obsolete

Written by: Kiley Nichols
4 min read

For the experts who build and support new technologies, life seems to be getting tougher all the time. With the demand for digital services exploding and the move to the cloud taking off –even more so since the pandemic – developers and support teams are working harder than ever to keep up.

Having spent the last 20 years on the front lines of the tech revolution, Robin Purohit understands the predicament. He’s CEO and co-founder of, a company that uses artificial intelligence and machine learning to help IT experts solve problems faster. 

“I’ve lived all of my career in business-critical software, and now, almost all software is business critical,” he says. “There’s so much demand to build cool things and transform businesses to become digitally native. There’s so much change happening so quickly.”

This increases the pressure on IT experts, who are tasked with not just writing good code, but integrating it, securing it and making it more resilient. “There’s so many things to be aware of now, that it outstrips the average developer,” he says. “There’s a lot of amazing ones out there, but for the average developer, it’s very tough.”

It’s even tougher for someone on the other side of the fence – namely, the typical software support person. This is an individual who probably didn’t write the original code but who’s still responsible for supporting an application that could include thousands of components built by scores of different people. For these support professionals, “there’s nobody to talk to, and yet you’re on the hook if something’s not working,” Robin says. “So, how do you solve that problem?” 

Purohit may have found an answer. Why not help experts solve their problems by tapping into the world’s biggest and best software development communities? “There is a lot of collaboration that’s happening among the development community,” Robin says. “If you go to these communities, you'll see hundreds of millions of engineers collaborating out in the open.”

One of Robin’s favorite tech communities is Stack Overflow. The site attracts more than 125 million users a month, most of them developers and engineers looking for answers to problems ranging from coding to cloud technology. “It’s a vibrant community with a lot of topics,” Robin says. 

This massive gathering of talent offers a rich venue for deploying AI and machine learning to help support teams, developers and customers track down the knowledge they need to solve a problem, build a new product, or learn a new technology. And they can do all that without opening a support ticket, saving time and expense.  

After all, the biggest companies can process millions of cases a year, Robin notes, and even a mid-sized tech company can get hundreds of thousands. “That’s not where you want to be spending your money,” he says. “You want your technical service experts to be working on the hardest problems, not the everyday problems.”

AI and ML assistants from can help you quickly zero in on the relevant, trusted conversations that community participants are openly engaging in. “If you’re a developer and trying to stay on the cutting edge of technology, you want to go to a place where you can get answers quickly,” Robin says. “So, you want to be the beneficiary of AI-augmented people who are empowered to answer your question much faster than before and without having to open a ticket.”

Robin believes the old ticket-based support model will soon shift to this more open collaborative approach to problem solving. “It should be the last resort when somebody opens a ticket,” Robin says. 

And there’s another advantage for people who leverage AI and ML to help solve thorny technical problems. “It boosts somebody’s ability to look good on a forum and improve their industry reputation and career prospects,” Robin says. “We’re trying to get more people to look like heroes and be unafraid to participate in these high-profile forums.”

Listen to more of Robin Purohit’s story on Episode 93 of DevOps Radio.

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