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Every company has a breaking point. A moment when an organization realizes it is overwhelmed by an avalanche of inbound calls and emails that bombard personnel with the same rudimentary questions over -and over again. It’s a vexing problem that resembles a scene from Groundhog Day, where team members feel as if they are constantly reliving the same day. But what if there was an easy data-powered solution to this problem? David Karandish is the CEO of Capacity, a company on a mission to solve those pain points through the power of A.I. On this episode of IT Visionaries, David details how the Capacity platform is eliminating common issues by using conversational intelligence and he explains why not all chatbots are serviceable. 

Key Takeaways

  • Does Not Compute: Not enough companies are using full-fledged platforms for their A.I. needs. When companies rely on single-use chatbots, those services are not able to escalate conversations to the next level. Instead, there is forced human interaction that otherwise is not needed with conversational intelligence.
  • Build vs. Buy: When embarking on a digital transformation, the first question should always be if you should build your own software or simply buy an out-of-the-box solution If the software is not core to your business, don’t invest resources into it.
  • Evolution of A.I.: The next step for A.I. is to become less reactive and more proactive. As more companies begin to utilize A.I. technologies, the wealth of data produced will continue to grow. Over the next few years, A.I. can go from simply answering questions, to being able to solve tasks for users.

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For a more in-depth look at this episode, check out the article below.


Every company has a breaking point. A moment when an organization realizes it is overwhelmed by an avalanche of inbound calls and emails that bombard personnel with the same questions over-and-over again. It’s a vexing problem that resembles a scene from Groundhog Day, where team members feel as if they are constantly reliving the same day. But what if there was an easy data-powered solution to that problem? 

David Karandish realized this issue during his time with his first company, Answers.com. After noticing his website fielded the same question multiple times over, Karandish began to ponder new ways to streamline the process. Determined to make the customer journey and the employee experience more efficient through data, Karandish began to develop an A.I. platform that could intelligently answer questions on multiple levels.  

Founded in 2017, David is now the CEO and Co-Founder of Capacity, a company on a mission to solve those headaches through A.I. Capacity is an enterprise artificial intelligence SaaS company focused on helping teams do their best work by automating the core functions of a company — emails, phone calls and IT tickets. According to Karandish, Capacity’s technology can answer 84% of all inbound questions that representatives receive on any given day. A number that continues to grow and excites him.

“What’s been so exciting about the platform is that every day, the A.I. just gets smarter and smarter and continues to take on more and more of your workflows,” he said. 

As a full-stack solution, Capacity has the ability to answer questions, automate workflows, and provide tickets.

“I love the fact that you can plug capacity into just about any part of the organization — your HR service center, your IT, customer help desk, even your own personal productivity,” Karandish said. “The most exciting thing about the platform is its flexibility and its ability to continue to grow within the organization as you roll it out to more places.” 

Karandish provided an example of how their service is empowering companies through A.I. One case study examined a partner of Capacity’s that recently entered a growth stage and doubled the companies size in a matter of months. At the same time, Capacity’s A.I. was able to help them reduce their calls to their call center by 25%, simply by answering frequently asked questions before the conversation ever escalates to human interaction.

But what happens when those calls get to to a support staffer and those same individuals provide a wrong answer? According to Karandish, their feedback loop helps solve those headaches. A feedback loop is a support system designed as a check and balance service to make sure the internal bots are learning as much as they can, while not accounting for misinformation.

“One of the most important parts of the system like ours is the feedback loop,” he said. “With every single response, we’ve got a thumbs up, thumbs down mechanism. A thumbs up teaches machine learning to match that response a little more often. Thumb it down and we will instantly send that over to a co-pilot or a support agent within the org. You can jump in and respond to that question.”

But just how widespread are systems like Capacity? According to Karandish, most companies fail to utilize a full A.I. platform. Instead, they lean heavily on single-use chatbots., which is something he advises against.

Karandish emphasized that while companies continue to implement more and more A.I. as a service platforms, many of them are trying out services that are not easy to get up and going and that don’t actually scale when you get into real-world use cases. Karandish stated that companies and consumers will begin to recognize the difference between a basic bot and a fully functional conversation A.I. in a matter of years.

“The reason that there’s so much excitement around this technology is that we’re finally at the point when your files are in the cloud, your applications are in the cloud, your knowledge is stored in the cloud,” he said. “So all of the pieces are there to finally create an intelligent cloud-based operating system to run your business.”

As those pieces continue to come together, Karandish predicted that A.I. platforms will begin to shift from being reactive to proactive in the next few years. And as the wealth of data continues to expand, and as the machines continue to learn, A.I. should grow from simply answering questions to taking on tasks.

“We will get past this us-versus-them mentality that a lot of organizations have,” Karandish said. “The shift from A.I. answering questions to A.I. taking on tasks will happen. As artificial intelligence gets better and gets better implemented, you’re going to see an exponential increase in usage because it’s going to unlock lots of economic opportunity, both in terms of cost savings and revenue generation all while creating a better customer experience.

So why should industry leaders begin the process of implementing A.I. strategies? According to Karandish companies that fail to deploy some kind of artificial intelligence over the next few years, will get left behind.

“If you are a technology leader and are not at least trying this out, you are going to be left behind very quickly.” he said.

To hear the entire discussion, tune into IT Visionaries here

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