Aug 26, 2026 · 25 min · 12 segments
For years, voice has been the channel most enterprises have quietly dreaded. The reason stems from it being harder to automate than chat. It's also harder to scale across markets, and far less…
Trisha PillayHost
And that is, can voice operate as a standalone experience? Because like you said, you know, it's all about the customer experience.
Also voice is so hard as well because it's multilingual, right? So how does this ultimately need to sit on the same platform and then just infrastructure as channels such as chat, messaging, web to deliver such a truly seamless experience for the customer?
I think that's a really important question and a very good question because this is one of the biggest problems we see when it comes to AI.
We actually met up with a client who has a 20-person team working on their AI while they have 10 people on customer service.
So there's something wrong with basically how sometimes people are really deploying, and that's because they're thinking of every channel as an individual channel instead of really thinking of it truly omni-channel.
And that's one of the things that we really focused on because we've been in this industry now for nine years.
And one of the biggest pain points is how can you make sure that you can actually maintain this? So not just build, deliver, but really maintain this and scale this.
And to be able to do that, you truly need to have one AI that can actually go across channels.
Also, what we've seen is people... do different AI solutions for every language as well.
So imagine the number of variations you have if it's going to be separate for every language, separate for every channel.
And that's actually been one of our USPs, which is, can we deliver you something that just works across languages, across basically channels? And that's kind of been a little bit of our claim to fame.
And that is, can voice operate as a standalone experience? Because like you said, you know, it's all about the customer experience.
Also voice is so hard as well because it's multilingual, right? So how does this ultimately need to sit on the same platform and then just infrastructure as channels such as chat, messaging, web to deliver such a truly seamless experience for the customer?
I think that's a really important question and a very good question because this is one of the biggest problems we see when it comes to AI.
We actually met up with a client who has a 20-person team working on their AI while they have 10 people on customer service.
So there's something wrong with basically how sometimes people are really deploying, and that's because they're thinking of every channel as an individual channel instead of really thinking of it truly omni-channel.
And that's one of the things that we really focused on because we've been in this industry now for nine years.
And one of the biggest pain points is how can you make sure that you can actually maintain this? So not just build, deliver, but really maintain this and scale this.
And to be able to do that, you truly need to have one AI that can actually go across channels.
Also, what we've seen is people... do different AI solutions for every language as well.
So imagine the number of variations you have if it's going to be separate for every language, separate for every channel.
And that's actually been one of our USPs, which is, can we deliver you something that just works across languages, across basically channels? And that's kind of been a little bit of our claim to fame.
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