In the episode, Guy Shalom, the CEO of Glassix, shared the personal story behind the company’s inception. Glassix began as a solution to a personal challenge: both of his parents have the same disability, which made effective communication challenging.
This experience inspired Guy to develop a solution that could improve communication not only for his parents but also for customers facing similar difficulties. Over time, this idea expanded and evolved, ultimately becoming Glassix—a company dedicated to improving the customer experience through advanced digital channels and messaging platforms. This journey from a personal challenge to a broader mission encapsulates the company’s commitment to making customer interactions more seamless and accessible.
Guy was joined by his Head of Product, Yoad Rashti and his CTO, Boaz Katan as I stretched my podcasting limits with three guests at one time!
🔹 AI-Driven Efficiency and Personalization: Glassix is revolutionizing how businesses interact with customers through AI-driven features like conversation summaries, chatbot AI answers, and mood interpretation. These advancements allow for real-time personalized responses, significantly improving both customer satisfaction and agent efficiency.
🔹 Cross-Channel Communication: With integration capabilities across multiple platforms like WhatsApp, web chat, Facebook, and Apple, Glassix provides a seamless communication experience. This multi-channel approach ensures that customers can reach out through their preferred platform, making interactions smoother and more effective.
🔹 Customization and Security: Glassix’s platform is not just powerful but also customizable and secure. Offering flexibility for various industries and compliance with standards like PCI DSS, the platform ensures that user data is protected while allowing teams to tailor solutions to their specific needs.
Catch the full episode for an in-depth discussion on how AI is shaping the future of customer experience and how you can leverage these innovations to boost your business! 🎙️
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Show Notes
- Guy Shalom
CEO & Co-founder, Glassix
Guy Shalom is the CEO and Co-founder of Glassix, a leading software company revolutionizing
customer service with its omnichannel interactive communication platform. Under Guy’s
visionary leadership, Glassix has become a pivotal player in the SaaS industry, providing
leading-edge digital solutions tailored to the needs of modern contact centers.
- Yoad Rashty
CTO& Co-founder, Glassix
Yoad Rashty is the Chief Technology Officer at Glassix, where his expertise in driving
- technological innovation and his deep understanding of customer experience technologies empower leading companies to deliver exceptional customer experiences. With a robust background in software engineering and a keen focus on integrating leading-edge artificial intelligence technologies, Yoad leads his teams in developing advanced, scalable, and a secure platform that enhances customer interactions for businesses globally.
- Boaz Katan
Head of Product at Glassix
Boaz Katan leads the development of an advanced omnichannel messaging platform designed to enhance customer experiences. With over 10 years of experience as a product designer in both startups and large corporations like NICE and NetApp, Boaz has a proven track record of designing complex B2B systems.
Contact Info:
For guest contact information, I recommend checking out the multiple platforms mentioned in the episode. You can reach out to the business through their:
– Website
– Web chat
– Facebook page
– WhatsApp account
– Apple account
If you prefer more direct contact information, you might want to visit the Glassix website or their social media pages for further details.
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Transcript
Note: This was AI-generated and only lightly edited
Mark Slatin:
Today on the Delighted Customers podcast, we’ll hear a story of an innovation born from a personal challenge. Glassix, an AI-driven tech company, originated from a spark, an idea that arose from the CEO whose parents both have the same disability. And he discovered a way to improve their customer experience and then scale that idea to help thousands. We’re going to call the topic how Glassix leverages AI to improve customer experience. And so many are in a race to try and leverage AI to to increase revenue, to grow share, to get market, to reduce cost, and what we’re most interested in, how could you improve the customer experience through AI? So today we’ve got not one, not two, but three guests on the show. This is me stretching my experience and my limits facilitating this. So I hope there’s grace in the audience for whatever happens today. But first, I’d like to welcome our first guest. Let me just tell you who’s on the show. We’ve got Guy Shalom, the CEO. We’ve got Boaz Khatan, head of product. And we’ve got Yoad Rashti, the CTO and co-founder. So, Guy, I’d love for you to, first of all, all three of you, welcome to the show.
Guy Shalom: Thank you very much for having us.
Mark Slatin: All right. So, so excited to have you and get into this conversation. Guy, could you share a little bit? It was a really fascinating backstory to how this company started. Can you share with us how Glassix began?
Guy Shalom: Yeah. Actually, I was on a time off from work. And I met Yohad through my previous CEO, actually, that introduced between us both. He told me, you’re a geek. He’s a geek. Meet up, maybe you’ll find something interesting to do. So we met, and each one of us had a list of ideas that he wanted to do. And I was born to two deaf parents. And as a young boy that spent a lot of time in contact centers over the phone to help his mom and dad, I thought, hey, we’re in, it was 2015. We can do something different. We can have video, images, text, and help deaf people to communicate. So we started thinking how to do that. We went together to my previous work base, which was very fun at that time. And we decided to do a pilot. And after doing that, we understood that video and images are assisting some, let’s say, technical matters. I mean, if you can see a payment terminal and the connections behind, you can understand more about the issue or the reason that creates the problem and you can also train the fix it easily using videos or images and we started doing that and in the second customer which was an AC company we saw another product which was around let’s say social multi-channel something like that and I told you out there Take a look at that. It’s, it’s interesting. It’s similar to what we do. Let’s take it to the next level. So we decided to redesign and rebuild the Glassix. We actually, we met Boaz back then through some Xceller Accelerator and boss gave us some UX UI tips and designed the first version with us and The rest is history. I mean we met only five years later But but he was actually the one doing the design back then and we’ve rebuilt the classics and started selling it This is the this is how we all started basically
Mark Slatin: So really interesting. And, um, and so your parents were, were hearing impaired, they were deaf and you just, you, you kind of, I mean, this, I have a friend who, whose name is Dennis Gielin, who’s in the CX space and he’s now helping entrepreneurs. He talks about this idea of, uh, happy accidents. You know, you kind of stumble across this thing and then you go with it and you guys were able to iterate from the original design and evolve to what you saw was an opportunity. So what is the product offering today and how is it different than your competitors?
Guy Shalom: So Glassix is a digital channels, conversations or messaging platform. We help businesses to communicate with their customers in digital channels. If it’s Facebook Messenger, if it’s Apple Business Messaging, if it’s WhatsApp, WebChat, TikTok, Instagram, whatever channel you choose to communicate with the business. will be there to give you the experience. The experience is cross-channel, meaning that if you decided to talk with a web chat from the website, you’ll get the chatbot. And the same chatbot can serve you in Facebook Messenger. We do it cross-channel. And if you started in a web chat and you can’t wait in front of the PC, so in one click you can replace the channel to be WhatsApp and continue in a fully different channel, the same conversation with the same agent. So this is what we do today with customers, and we try to do it intuitively, fast. We try to make the best agent experience that we can. We try to assist agents to answer to customers as fast as possible. If you try and think about chatbots, we all know chatbots as the starter of a conversation. When a customer gets to a chatbot, chatbot tries to solve the problem. If the problem isn’t solved, then he’s going usually to an agent. and he speaks with an agent and let’s say that he had a car accident and he needs to fill a report. So the agent usually has a script asking this, asking that, send me the picture of the car, who was involved, what time was it. So instead of doing that, we do that different. We allow agents to send customers to chatbots during the conversation. I mean, this is a script, but why do I need to occupy the agent in the script? A chatbot can do that instead of an agent, and the agent will be available to answer another customer. And when the customer will finish filling the report with a chatbot, he’ll come back to the agent. And this is a big difference in understanding chatbots. And these chatbots can be traditional AI chatbots, if it’s generative AI. if it’s a or if it’s a intense and empty design. Fully flexible.
Mark Slatin: Got it. So you’re bringing some efficiency to the agent and in the process, improving the experience for the customer because they could do a combination of live plus self-serve at the same time.
Guy Shalom: Exactly.
Mark Slatin: Yeah. So, Yoed, can you share with us what’s available now and what’s in development at Classics in terms of solutions?
Yoad Rashti: Our main focus, shockingly, in the past year is AI. In the past two years, there was great development in AI. It’s remarkable. Things that AI can do now, three years ago, it was like, if someone would have told me that, I would have laughed. I wouldn’t believe them. So what we can do today really enhances the agents. So the things we do today. simplest thing, conversation summary. That’s not complicated, easy to understand. Instead of the agent to manually type the summary of the conversation you just had and to insert it into the CRM, AI can do that automatically. Next thing we do is chatbot AI answers. So The really interesting features of AI today, they’re built on top of a knowledge center. and knowledge hub. And that’s the critical part of AI. If you want to have AI to work best along your agents, you need a good AI knowledge center. This can come from this data, this knowledge can come from your websites, and then we can crawl your website using web crawlers. It can come from files, PDF, Word snippets, just like simple text you can insert to your customer to the Knowledge Center. Another interesting thing that we do, we read the ongoing conversations and we parse these conversations, the conversation history, and extract questions and answers from them. So we’re also inserting that data into our Knowledge Hub. And after we have all of that knowledge, now the AI can kick in and start answering customer questions. So as long as the answer is there, probably the AI chatbot will be able to answer that. And that’s amazing. Another thing that we do that really helps is integrating
Yoad Rashti: live the information about the customer and kind of inject it into the AI. And basically what exactly does it mean? It means that when a customer comes and starts a conversation with you, You can pull data about him, like his name, his current subscription status. Is he happy? Is he not? Is he a returning customer? All of this data, and you can inject that to the AI. And then the AI can base its answers on that data. So that’s something that works really well.
Mark Slatin: And then today, how would you describe the product offering that you offer your partners?
Guy Shalom: So basically, as I said, so basically, we tried, as we said, customizable and flexible, we tried to do the platform as cross vertical as possible. I mean, today, if you take a look at the customers, we have retail, we have e-commerce, we have appliance, we have municipal and government, you’ll find insurance, fintech, automotive, and you’ll find hospitality, logistics, everything. If you take a look at the size of the customers We you can find a local grocery store and you can find a big telco using the same platform the same features it’s I mean when we when we provide a platform to a customer when we provide a Environment to a new customer it comes ready-made with all the settings all the messages all the SLAs Everything is defined already automatically according to market standards And then the customer can customize if it needs this tweak or that tweak, you can do it on its own. And we’ve also built the tools to be able to share customizations. I mean, if customer A built an amazing chatbot or partner A built an amazing function in the, I mean, amazing piece of code and function of integration to Salesforce, you can export import. and exchange this data between customers that create a community of people sharing know-how and solutions from the platform.
Mark Slatin: So you’ve got sort of this cross-innovation across your customer base in an open sharing model.
Guy Shalom: Yeah, exactly.
Mark Slatin: So if I’m a VP of CX or a customer success leader, maybe I’m the COO, why should I invest in your solution? How am I going to sell that to my C-suite?
Guy Shalom: Okay, great question actually. There are a lot of reasons and usually in this kind of decision you also involve the CIO, you also involve let’s say security teams. I mean it’s usually a big decision. usually five to ten people at the room and When we talk about what we do differently, so first of all, we’re all about Saving time and saving time one is is the implementation process. I mean when we create a customer today the let’s say the platform is up and running in 30 seconds and Okay, when you want to connect an inbox, it takes you about 15 to 20 seconds. I mean everything is fast easy When you launch and implement and customize your platform second thing are the agents and for the agent that I think I’ll let others speak today, but We try to do everything to make the agents work as let’s say fast as possible if it’s helping them getting the data to answer the customer if it’s Summarizing in one click conversation and other features that help shortening handle time and parallel Paralyzing work together. I mean, I want my agent to be able to respond to as much tickets in parallel And this is why we try to focus and this is where Boaz kicks in with good user experience as well. It’s very important for us. And if we take a look about how contact centers are training new team members. So a lot of products they’re built to train people and new people, let’s say, listen to conversations and and grade them and everything, but eventually when you take AI and you suggest new agents with answers from experienced ones, then you teach them, you do what we call on-the-job training. And this on-the-job training actually allows new agents to start replying very fast. And eventually, what’s more to that, that we add a lot of analysis capabilities. I mean, if we take a look at Glassix, we provide, of course, an Excel-based report. That’s great. We provide online dashboards that you can customize. That’s great to manage the team. But we’ve also went one further step, and we integrated Microsoft Power BI within Glassix. I mean, so today you don’t have to integrate the conversations and KPIs into your BI system. It’s already inside. So we try to give a 360 view to all teams, if it’s analysis team, if it’s management. It’s the CX or CIO and one less thing is security. I said very fun earlier So PCI DSS was my daily breakfast payment terminals retail platforms payment gateways So we invest a lot of time and money in security and this is something that you won’t find Usually in other platforms in that depth OK, so this is another important decision making when buying such a solution, because today everything is in the cloud. So it’s very important to to keep privacy of your customers and information and other.
Mark Slatin: That’s it. So so you’ve designed a solution that if I’m if I’m trying to sell that, number one is or if I’m if I’m the customer, it’s easy for me to get my team to get ramped up to use it. It’s going to be connected to my other systems and integrate all the information so I get a 360 degree view of the customer relationship. It is offering what we call MBA or next best action. for the customer, the call center agent with now tools like video clips and images that they can look to help them facilitate the conversation. Again, going back to speeding things up and making the job easier, not only for the customers, but for the employees. which obviously would help with employee retention. So I’m going to be talking about happier employees equal happier customers and equipping these employees with way more information to help the customers with information before that they’d either have to look seven different places or they have to get back to a customer or wouldn’t even have the information. And now it’s all integrated. So at their fingertips, so they can make the customers happy. Am I characterizing that correctly?
Guy Shalom: Exactly, and I think that you all will talk about it later, but when a conversation ends, what Yoad’s team is doing, Yoad’s team, Yoad’s code is doing actually, he’s analyzing the conversations using AI models, extracts agents, let’s say, answers or suggestions to customers, and you’ll find this answer 10-15 minutes later being automatically suggested to other agents when a customer asks more Same questions. So we train our knowledge base from agents replies and we offer new agents or existing agents with already with ready-made responses that AI already created and In addition, when we suggest a reply to a customer, we also let the AI model read the full conversation. So if the customer is frustrated and asking a question, then we’ll try to talk about his frustration first and ask for his forgiveness and then give the reply. And the AI model will create the full answer dynamically using the customer name or the customer mood and everything to create the best answer for him.
Mark Slatin: Interesting. So, um, so AI is doing like a voice voice analytics, uh, from the recording or text analytics from the recording that came from the call and then giving them a way to handle it. It’s really interesting because, um, we’re, we talk a lot about personalization and I, I mentioned before the show, I was talking to you, Adam Boaz about the course I teach at Michigan state, which is customer relationship management. And that’s focused on from the point of the customer makes a decision to purchase, to engage with the company, to move them through the cycle, which would start with service after they’re onboarded. And this would involve things like the call center and the relationship manager and how they deal with issues when they interact with the company. And if they do a good job, then they move to loyalty on this. And then if they do a really good job and build the loyalty after a while, they become advocates and they go to advocacy, which is the last phase where they’re actually referring you out to their friends and colleagues. And they’re also willing to forgive you when you make mistakes. So as I think about your solution, and I’m trying to put the hat on of the let’s say the CFO, the CIO, people making the decision on why should I, why should I get involved in this? We’ve already made some good, good cases, business case is for it. But you mentioned Boaz earlier and Boaz is the head of product. And I’d like to shift it over to you Boaz now and ask you a question, which is, Could you describe some of the specific applications and how they’re used to improve both the employee and the customer experience? Can you share that with us?
Boaz Katan: So first of all, regarding the end customers, I mean, the company can solve the problem. I mean, I think Yoad will will tell much more about it, but the company can solve the problem even before it got to the agent. I mean, with using AI and we can push some customer details. For example, the customer, as you mentioned, he says he has a problem with his balance or something like that. He will ask, I don’t know, he will ask, I have a problem with my balance. And we will know the customer detail. We will push it into our AI module, and then we’ll give him an answer about his problem. And basically, the interaction will end there. So we will try to solve it even before it gets to the agent. The minute it got to the agent, I mean, something went wrong in the process and the agent will receive all the details he has on the specific customers. He will get, for example, he will get all his details from the CRM. He will see all the history of that customers. And of course, we will help him using AI to give the best answer. And so in that way, we also help the agent to resolve the problem.
Mark Slatin: Yeah. So, Yoed, can you share with us what’s available now and what’s in development at Classics in terms of solutions?
Yoad Rashti: Right, so our main focus, shockingly, in the past year is AI. In the past two years, there was great development in AI. It’s remarkable. Things that AI can do now, three years ago, it was like, if someone would have told me that, I would have laughed. I wouldn’t believe them. So what we can do today really enhances the agents. So the things we do today. Simplest thing, conversation summary. That’s not complicated, easy to understand. Instead of the agent to manually type the summary of the conversation you just had and to insert it into the CRM, AI can do that automatically. Next thing we do is chatbot AI answers. The really interesting features of AI today, they’re built on top of a knowledge center. and knowledge hub, and that’s the critical part of AI. If you want to have AI to work best along your agents, you need a good AI knowledge center. This data, this knowledge can come from your websites, and then we can crawl your website using web crawlers. It can come from files, PDF, Word snippets, just like simple text you can insert to your customer to the Knowledge Center. Another interesting thing that we do, we read the ongoing conversations and we parse these conversations, the conversation history, and extract questions and answers from them. So we’re also inserting that data into our Knowledge Hub. And after we have all of that knowledge, now the AI can kick in and start answering customer questions. So as long as the answer is there, probably the AI chatbot will be able to answer that. And that’s amazing. Another thing that we do that really helps is integrating live the information about the customer and kind of inject it into the AI. And basically what exactly does it mean? It means that when a customer comes and starts a conversation with you, you can pull data about him, like his name, his current subscription status, is he happy, is he not, is he a returning customer, all of this data, and you can inject that to the AI, and then the AI can base his answers on that data. So that’s something that works really well.
Guy Shalom: I think that if I may interrupt, you talked about a bank and a customer. If a customer comes and say, hey, I thought I have 32 pounds, but I have 28. And if we inject your balance in the past month, we tell you, hey, you had 32 three weeks ago, but you did this transaction, and now it’s 28. And this is a difference. Because if you take a look at Generative AI and say, hey, I think my balance is incorrect, Generative AI would usually send you to a URL to your bank account to try and figure out on your own or to an agent and when you inject the last transactions to Generative AI it can explain you about the exact situation and I’ll hand it over back to you.
Yoad Rashti: Okay, and the next really cool feature that we have is the agent suggestions. So during the conversation, if the bot, the AI answer was not able to answer the customer, usually he’s being transferred to an agent, real live human being. And so we try when we can suggest answers to the agent to save him time, very similar to how you have on Outlook or Gmail, only way better and focused and trained on ongoing conversations.
Mark Slatin: So let me just, if I could double click on that, because again, we’re interested in moving the customers from not just satisfied, but to loyalty, to advocacy. So they’re sharing, you know, they’re sharing how happy they are with their friends and colleagues. And you mentioned the word, the word happy, we can tell if they were happy from their history with us. So that’s always been a stumper, other than doing a offline email survey off a survey platform, for example, and then having to the challenge of integrating that, which is a totally separate platform and sometimes third party platform. How do you know if the customer’s happy? Like, let’s say it was the insurance person. They’ve gone through the initial parts of the claim process. Now there are two or three steps down the road. How do you know on that third step if they’re happy or not?
Yoad Rashti: Basically, it’s very similar to how can you tell if someone is happy? You can tell it according to his tone, the words he’s choosing. You can just tell. And so can AI.
Mark Slatin: So how does AI pick up the tone? Does it have the ability to check voice inflection and that sort of thing?
Yoad Rashti: Well, AI was trained on a lot of conversations, a lot of data. And so it can pick on the mood of the customer, the way that he’s speaking, almost as good as a human being, sometimes even better.
Mark Slatin: OK. And then obviously, it includes the language they’re using, the specific word choices, right? Yeah. Well, there have been a number of people beating the drum in the ex-professional world, not just in the US, all around saying surveys are dead, AI is going to take the place of that. What do you say to that?
Yoad Rashti: No, I don’t think so. I think surveys are very important. I don’t think they’re going anywhere in the next five years.
Guy Shalom: It’s also important to understand that we have built-in service in Glassix, so we can connect between the contact and between his past service as a part of the real data that we inject to the AI engine. And on top of that, if the customer is using an external service platform, then when we come and fetch the information, even during the chatbot about the customer, we usually ask for the past service result and we send them to the AI model on top of, it depends on how many question marks does he add and how many enter and clicks does he have. So all of this allows the AI actually, not us, to better understand the mood and the type of conversation.
Mark Slatin: Well, this is exciting because You know, as those of us who are CX strategists, advisors, consultants, and just get it, we would like to see AI being used to improve the experience customers have. And like you said, companies can focus on innovation and new ways and things outside the box rather than just putting out fires and playing whack-a-mole. So a question I have for you, Guy, which is, what do you see, since you’re the CEO, as a vision for Glassix and where can you apply AI to improve both employee and customer experience?
Guy Shalom: So basically if we take the last thing you talked about is when we analyze the conversation to improve the knowledge of the AI, then we do it and we can connect it to the survey results. If the customer was happy from the experience that the agent gave him, then we can give extra credits or score to this specific answer. And this is how you can improve the customer experience and create a loop of auto-training your AI model according to the response of the customer eventually from the ticket. And this is not just having a knowledge center. It’s even the tone of the answer. I mean, when AI, let’s say, analyzes conversations, he tries to keep the tone of the agent because this specific ticket had high scoring. This is a very important tool. I think that another important thing in AI is Analysis and generative AI Can do something differently. I mean it can I don’t know if replace but analytics are a great thing to do there I mean we’re doing a small experiment nowadays and we were able to do two things one we were able to See how happy are your agents? Okay, meaning that we could create a connection between the performance the customers the survey the handle time the response time and the amount of messages and predict predict the I mean the the end customer happiness and even predict if agents are going to leave the contact center so and this is a It all depends on the prompt that you give the AI. The question that you ask him, you tell him about the information you’re giving him and say, okay, try to find a model or try to give me a digest about my problematic agents, assuming you have all this data. And AI is going to take us to a place when we can see trends, push a lot of information via Excel files or everything to AI. ask to analyze and to bring us things that human beings don’t usually think of. And this is super interesting. And I think it will affect customer experience. You can do that for service and the answers. And you can find that this tone is better for these customers in this specific vertical. Or, I mean, it can change the world. And we’re now just investigating the capabilities. And as you had said, it evolves very fast. Things that we couldn’t dream of a year or two ago or things that have cost 10 times more are now very accessible. I mean, if you take a look at generative AI, there is something called fine tuning, when you can teach the AI model things from your information and not just bring in a specific data, just training the model. And if it was super expensive just six months ago, today it’s almost free. The world is going there and customers will build their own AI models and they can do it super fast because when I come into an existing customer and say, okay, I need to train you, I click and I take the last 10k tickets, digest them in about 10 to 15 minutes automatically and I have an AI model. That’s it. This will all improve both customer and agent experience because think of you as an agent instead of thinking make a mistake writing everything comes on your screen and you just have to Send or click change your world Award and then send it and this is what AI is going to do to customer experience agent experience Everything you you can dream up
Mark Slatin: Yeah, and it’s, you know, we talk about moving from loyalty to advocacy and what can really make a difference. And when you start getting, you know, hundreds, thousands of call center employees, and you’ve got a larger call center, there’s almost no way to say, well, you’re going to have a dedicated team, you’re always going to speak to Yoad or Boaz, you know, that’s that doesn’t become economically feasible. So then what you have is really a stranger calling in every time, which You know, historically, you don’t know a whole lot about. And now what you’re talking about is serving up some really good, specific information all the way from not only just their transaction history, but their mood, the best way to talk to them if they were unhappy in the past, you know, they might be unhappy. So it gives you some some direction as to how to communicate with them at your fingertips. You’ve got you know, the historical data of why they may have, what cases they may have had in the past, right? So that is a huge shift from where we were even just a few years ago.
Guy Shalom: Exactly. Even a few months ago. I mean, we’re working on AI 24-7. We have about four team members doing improvements and tasks, and because we’re a small company, I mean, just today, me, Boaz, and Yoad were in the room, and in, I think, 15 minutes, we changed how agents will see the suggestion. In the screen, we say, Hey, I think it’s much better. Boaz went to his room, sketched something, and I think it’s going to be to next Thursday version. So this allows us to adopt. I mean, if you take a look at the GPT, they are releasing new agents all over again. And GPT 4.0 Mini was released to Azure three weeks ago. It’s live next Thursday on our platform because It’s cheaper, it can give you a lot more capabilities, and you can use it broadly. And this is what’s different, again, about Glass6, and this is why we recommend big companies take us, because we focus on future and innovation.
Boaz Katan: Go ahead. And connect to that, that when we started to make and build the knowledge-based AI, it was not long ago, and I mean, every week there is some change. And I want to connect about the user experience as well, and the value that we give to the customers, that we build everything Uh, very, very, uh, uh, uh, intuitive. I mean, it’s very, very simple. We’re trying to, to make everything simple. So even the smallest, uh, uh, company can use it, uh, as well as the biggest, as the biggest, uh, enterprise.
Mark Slatin: Uh, that that’s, that’s helpful to know Boaz. So it’s, it’s scalable and you don’t have to worry about being too small of a, of a customer to use it. Um, I want to ask one more question then. Um, and I want to, if you don’t mind sharing how people can get ahold of you, but this question’s been, uh, sort of the elephant in the room from, and I’ve heard it from, uh, people through LinkedIn and other conversations they’re concerned about. Um, they’re concerned about people losing their jobs, especially in the call center, but maybe other places. So I’d like to get your take here in the last couple of minutes, as much as I’d like to talk to you for much longer. We got to land the plane here. So could you share, you know, there’s a fear and also, like, what would you say to the CFO who is looking to take costs out of the system?
Guy Shalom: I’ll answer this question. I mean, there are a few things. It’s true that AI can sell tickets faster than a chatbot. can shorten handle time but When you give good service People contact you even more. This is one thing second thing is that digital channels have Raised the amount of tickets at about 20 to 25 percent in specific verticals I mean people are lazy to call over the phone and not and wait while they can just Message you via your phone and wait for an answer and response back to you After 10 minutes, they do it during the work. So this is the second thing. And the third thing is that contact centers will always have work. And I had a customer that had a 100 agent contact center. They did something very cool in their chatbot. It’s a telecom company that pings your router at home and tells you, You have a problem with your router, please reset. This is your model. This is the video how to do that. That’s great. So they could actually send 18 people home at the first day when the chatbot went live. But what they did is to improve the response time instead of sending these people home and say, hey, we’re not responding in five minutes. We’re doing that in three minutes. That’s better. And when a CFO tries to save money, that’s great. But reducing response time and getting happier customer, I think is much more worth it. So I don’t think people, I don’t think agents are going to lose their job. Analysts and other stuff. I don’t know. It’s a different conversation. We can talk about it on a different show.
Mark Slatin: Right. Right. All right. Well, that’s great. That is really helpful. Um, and so exciting to hear about what you guys are doing, to hear about the latest, uh, and greatest and kudos to you for doing so much so quick and, uh, love the backstory of what you’ve done, a mensch guy to help your mom and dad out who are, who are deaf. Uh, but it germinated the whole idea for the business. And I could tell people working on your team are very excited about the mission that you’re on.
Guy Shalom: Exactly. Yes. I mean my parents are happy customers. They speak with contact centers all over Israel Using what’s up and using web chat and I’m happier usually when I come for the weekend Hey, I use your platform this week chatting with this and that and that’s a great feeling Yeah, that’s that’s awesome.
