In this episode of the SourceForge Podcast, we talked to Avi Kedmi, CEO of SysAid, about the integration of generative AI into IT service management. He explains the unique offerings of SysAid, the role of AI in enhancing service delivery, and the competitive landscape of AI in the ITSM sector. Avi shares insights on the evolution of AI within SysAid, the company’s recent achievements, and his background in AI technology. The conversation concludes with thoughts on future trends in AI and its implications for the industry.
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Show Notes
Takeaways
- SysAid focuses on mid-market IT service management solutions.
- Generative AI enhances operational efficiency and service delivery.
- Conversational interfaces are key to user-friendly AI interactions.
- AI can automate and streamline IT support processes.
- SysAid’s product was launched after extensive beta testing.
- The company has seen significant client adoption and success.
- AI’s potential is vast, but requires careful implementation.
- Avi Kedmi emphasizes the importance of user feedback in product development.
- The competitive landscape is shifting rapidly with new AI entrants.
- Understanding AI’s implications is crucial for future innovations. Teenagers will use AI to generate unique content.
- AI is democratizing access to information and tools.
- Virtual agents are set to revolutionize task automation.
- Security is a constant concern in IT management.
- Integration of AI solutions is expected by users.
- MTTR is a key metric for IT success.
- Service management can apply to diverse industries.
- Entrepreneurs should act without waiting for the perfect time.
- AI will reinvent existing products and services.
- Passion and knowledge are crucial for AI entrepreneurs.
Chapters
00:00 – Introduction to SysAid and Generative AI
03:05 – The Role of Generative AI in IT Service Management
05:59 – Innovations in Conversational Interfaces
09:00 – The Competitive Landscape of AI in ITSM
11:55 – Achievements and Recognition in the AI Space
15:04 – The Evolution of AI in SysAid
17:51 – Avi Kedmi’s Background and Insights on AI
20:52 – Future Trends in AI and IT Service Management
23:48 – The Evolution of AI in Education and Industry
26:59 – The Rise of Virtual Agents and Automation
32:36 – Security Challenges in AI and IT Management
35:18 – Integrating AI: Challenges and Opportunities
38:33 – Tailoring Solutions Across Industries
41:56 – Advice for Young Entrepreneurs in AI
Transcript
Beau Hamilton (00:05)
Hello everyone and welcome to the SourceForge Podcast. Thanks for joining us today. I’m your host, Beau Hamilton, Senior Editor and Multimedia Producer here at SourceForge, the world’s most visited software comparison site where B2B software buyers compare and find business software solutions. Today we’re talking with Avi Kedmi, CEO of SysAid, an IT service management platform that integrates Generative AI (GenAI) into all aspects of service management. They’re a really exciting firm to watch in the quickly evolving AI space, just working to, to really enhance service delivery for clients and operational efficiency.
And I always like to tell people that we’re entering the efficiency era with all these different new AI tools we have available now. And so I think companies like SysAid are really just reaffirming that with what they’re doing. without further ado, Avi, welcome to the podcast. Glad you could join us.
Avi Kedmi (00:54)
Thanks, happy to be here.
Beau Hamilton (00:58)
Happy to have you here. Yeah, so can you, just to kick things off, can you give us a high level overview of SysAid and some of the solutions your company provides?
Avi Kedmi (01:07)
Sure. SysAid plays in the, what they call, service management market. Service management is mostly known for products that are out there to support employees. Could be employees that needs help with IT, employees that needs help from the HR team, employees that needs help from the finance team. And it’s called service management because it’s, it’s product, these are products that are servicing the employees. We provide, our uniquenesses is that we provided with mostly focused around mid-market. And also the way we provide it is with no code and a way for you easily to get up and running, be live and get the value, and make the changes you need comprehensive and at the same time without a cost of doing it more about drag and drop.
And about a year plus ago, we founded journey of generative AI. And since then we’re going to roll off something I think really interesting. And I know we’ll talk more about it, but at the core of it, we’re providing service management, specifically IT service management focus for organizations that are mid-market.
Beau Hamilton (02:29)
Hmm. Yeah. I think you’re really in an exciting time for the industry and you know, I, I haven’t used your product, but I’ve, you know, I’ve used a good handful of different generative AI products, consumer facing ones. I just think of, you know, from OpenAI, from Anthropic, Gemini, and the, the conversational element where you can just type in and plug and play sort of, and generate your own prompts and actions.
It’s just super user friendly. Is that kind of something that’s really baked into your product? Could you see a similar interface?
Avi Kedmi (03:05)
Yeah, I’ll tell a story. I joined SysAid about a year and a half ago, a bit more. And when I was approached to take the CEO role, I thought what are the true main reasons I felt like SysAid is such a good match for me and interesting play. And the biggest reason for my arrival was, I think that this world where SysAid is playing, generative AI is like, you know, bringing a kid to a candy store. It’s because IT service management is a place where you have in your hand all of the data to create a fully AI contained environment, right?
So think about when someone needs help from IT, then you have in the systems all the tickets that ever were created with the IT department, all of the conversations. And also within the tickets, there is something called in the ITL practice, solution resolution. So if you do it well, when you summarize the ticket, you also internally summarize how did you solve it? So next IT person will know. You also have all the knowledge-based articles that are existing, that exist in the, in this product and like how to install VPN, how to ask for a new computer, how to fix, you know, repeating things. So you have it within the system itself.
And the next piece is within this product, which many of these products that are service management, you also have all of the rules, escalation rules, email rules, workflows, approval process that are built by the company into our system. And the last piece is many of the vendors like us also provide what you called asset management. So we provide to all of our customers, we provide an executable that runs in the employees’ laptops that monitors that. So when someone opens a ticket and say, my computer is slow, then the person getting it also can look it, automatically match the computer of the user. And then the IT agent would say, interesting. see that he installed something that he shouldn’t install, I need to talk to him and how we didn’t know it. It’s not going to take 20 minutes to log in remote. just sees it. The data is there. You have it all. Think about generative AI. You have all, you can tell me you have a problem. I can understand it. I can give you a solution and I can also run shell script on your computer, all by AI.
So that’s why I joined SysAid. And also that’s what we’ve been focused on. And we’ve introduced two main, so just to, for those don’t know a lot about GenAI, it’s a lot of chatbots, right? Chatbots, chatbots, chatbots. So the first thing that we’ve done is we’ve put in the front for employees and for IT agents, conversational interfaces, right? So, it was the revolution of GenAI is first is it’s, just moving to a conversation and a chatbot versus it is something else.
And doing so we started to add more and more capabilities. Like the first thing would be if you want a ticket, there is an agent, you can ask, Hey, what should I do here? How should I solve it? And the second layer would be, Hey, I see that this is a person that his last name is wrong and I need to fix it in Azure someplace in the LDAP. So the AI would say, can I run that script for you or can I just go there and do it for you? So this is evolving starting with these conversational interfaces and now the capabilities that the AI is doing more and more to help you.
Beau Hamilton (06:29)
That’s really interesting. Yeah. It sounds like you not only have like a glossary and, FAQ kind of built in, but you also, have a specific client information built into the, to the conversational chatbot. That’s, that’s huge. and also I know you kind of tease the, the AI agent, kind of maybe future version of your product or maybe something you’re, you’re having beta.
Avi Kedmi (06:55)
No, no, we have already, we, so we’ve launched the product in January 1st this year after a few good months of beta. We have, I think around 160 clients that paid for it in 10 plus months and like live working. It’s been amazing. We started by the employee chatbot. We added an agent chatbot and soon we were starting with these clients, the beta of the agent AI.
But we’ve seen tremendous success. And like I said, I think it’s, it’s, it’s a lot about the opportunity that exists in ITSM, but at the same time, you have to do it in a way that you do not require work from them. You know what I mean? Like these are not enterprise that every project comes with like a big budget and integrations and a lot of money.
Beau Hamilton (07:41)
Yeah, yeah. I imagine it’s costly to build out and you’re probably also always at odds of like, you maybe partner with an established AI company or work together? Do you kind of develop it in-house? I imagine that’s something you’re kind of always looking at.
Avi Kedmi (08:00)
So I think, you know, when someone asked me last April, a year plus ago, you know, he said, you know, but the AI is not perfect yet. Maybe we need to wait. And I said, there are thousands of developers in OpenAI, in Anthropic, and you want to ride on their wave. You will see because where the technology is now, it’s not going to work. It’s going to be in a year.
And it’s not even, you cannot dream where it’s going to be in two years or three years. But if you start riding on it, but to your use cases, this is a storm that you’re going to be part of. For example, there was one morning where for OpenAI 4o went live and we went to our clients and we said, we’re updating in few days our AI. And suddenly all the answers will double like half the time it took us to reply with an answer. The AI took now half the time because, because they made the job. And now there’s a big jump around writing code, and they’re going to benefit from it also.
So we use any OpenAI APIs for different APIs to our needs, summarizations, categorizations, generating responses, and things like that. With code, we’d mostly use Anthropic. They’re doing a great job. And we do once a month different testing with like Lama and others like Gemini and trying to see, but we see who gives the best answer and we stay with them for a few months and then we try it again. So, but for now, these are the ones that we mostly use. And we have an architecture that organized the content correctly for the AI to use it correctly, right? Because let’s say you have now five years of tickets and someone asks a question. How, like, if you don’t store it in a way that it’s refreshed correctly, then you may give an answer that’s wrong, right? You want to hear an example of it?
Let’s say someone comes in the morning and they come and say, hey, the electricity doesn’t work well. I think, like the heating, something is wrong. And I’m in London and I’m freezing in the office. So the agent will come back and say, hey, by the way, people are on it. In two, three hours, it’s going to be fixed. Second person, let’s say it’s a company, second person comes to the office and he writes to IT or open an email and send them an email. Hey, it’s freezing here, right? In this case, the AI needs to answer already. Hey, we’re on it. You don’t need to a human for it. But let’s say four hours after the AI and let’s say the issue was fixed. The AI needs to tell it it’s fixed. Or if someone talks about it’s cold or something in the day after and it’s related to something else, the AI cannot answer to it. We’re on it, because it’s not something that you want.
So like all the ability to understand the data and to understand what to refresh the data and what’s not has a lot of power because at the end, the generative AI, what does it do? It tells you, give me five answers or 10 answers and I will generate the best answer from them. It’s not telling you, give me 20,000 tickets. I’ll know what to answer. It doesn’t work like that.
Beau Hamilton (10:54)
Gotcha. Well, that’s Yeah, that’s interesting. I appreciate that, like, unique example there. I already, I already love the stories here, because when we just got started, like, I want to know what? I know you won the Generative AI Product of the Year award by a global media company called TMC. I think that’s one heck of an accomplishment.
I cover, you know, this, the AI industry over on Slashdot largely from like a macro standpoint, but also, you know, cover some of the bigger consumer facing brands. And there’s no question. mean, this, this so there’s billions of dollars being poured into this industry. The fact that you guys were able to be highlighted in this way and these in these two different ways here, I think that’s really exciting. What, what do you think? Why do you think you were awarded for this product over your competitors? Like what makes your product really stand out over the rest?
Avi Kedmi (11:44)
So I think first we start, if you put aside ServiceNow that I respect a lot, amazing company, I think just the rest started late. I think they were, they started late. So I think they’re coming late to the game. So that’s one. Second, I think people tend to ignore or misunderstand AI and they bring it as a way for hey, this will answer all your questions. And we’ve built it from day one in a way that the IT leader can fine tune, monitor all of the answers, correct them, you know, and configure different things in a very easy manner. So I think that we came with the right approach of you deciding which data is part of this chatbot, which data is relevant and can be answered, which is not okay to use and all the fine tuning that you need.
So this brought a lot of trust into those using the tool. And the last part is UX. In the world of today, if you need to do a lot of, you just need to do a lot of work to get value. It’s just a lot of people stop at the middle. So it’s, we’ve built it in a way it’s plug and play in our system. It’s like a checkbox. Once you checked it, as you bought this aspect of our product, then it does it all. just takes all the data, cluster it, organize it, refreshes it in real time and from that moment. So I think that’s what made it unique. These three points, coming early, doing it correctly, and also understanding that it has to be out of the box and not too much hand-holding.
Beau Hamilton (13:14)
Yeah. Yeah. Well, I mean, if you have competitors who are, took the philosophy you, you thought about, you know, of waiting for AI to be perfect and ready, then they would have, you know, they’re just going to be left behind. They’re going to be still stuck in the incubation phase. and they’re not going to be off the ground, like, and running, like you guys are kind of working to, just keep innovating and, kind of going, going with the flow in a sense.
Now, from a history of your company standpoint like what? Were you guys always leveraging AI in the IT market or was this something that you added somewhat recently? What was your vision there?
Avi Kedmi (13:56)
So I’m only a year and a half plus in the company, so I can speak on my time. There were all different tries of AI prior, but pre GenAI companies, just to give a bit about, SysAid has more than 3,000 clients in more than 100 countries in the world, and double-digit growth, profitable, like we’re really seeing a lot of success. But at the same time, I would say it’s still a 20 years old company, right? So there have been different tries. Pre GenAI, it was just hard to be successful with AI if you haven’t had enough capital to do it. You know what I mean? You needed big teams of data scientists. You need a big data manipulation work to do. It just was very hard. And the output was okay-ish. Using GenAI just accelerates a lot of it in a different manner as long as you know how to use it correctly and build the architecture correctly. But so we’ve tried it in the past and it wasn’t good enough.
Beau Hamilton (14:57)
Okay. Now what’s your, what is your background? Cause I know, I mean, you say you started about a year, almost two years ago now, working with SysAid aid. that’s, I mean, that’s really when AI and the, the kind of, conversational AI chat bots really started taking off. Do you have a background in artificial intelligence and, and, tools like this?
Avi Kedmi (15:17)
Yeah. So I’m, I’m an engineer at the heart. Call it, 25 years ago, 20 plus years ago. Let’s stay there. I don’t put time on it. But engineer at my core and I had from 2005 to 2012, I had a startup that I’ve built with a great set of people that we built pure play machine learning technology, wrote it in MATLAB, moved it to Java, in the world of algorithm called predictive modeling and so I had quite a bit of experience. We wrote the patents, the patents that were approved. And from there, I went to work for a LivePerson that acquired the company we were building. And there I had 11 years as an executive that a lot of things related to the NLP worlds and language models. So I would say about 20 years experience with AI.
Beau Hamilton (16:10)
Oh wow. Okay. And yeah, you were, I mean, working with AI before it was AI. I imagine, you know, it’s a different terminology.
Avi Kedmi (16:17)
Yeah. People ask the people, the biggest lesson learned for me from like after the first two years with AI, call it many years back is AI can see a hair 20 miles ahead and it can miss a tree that stands in front of it. So, so this was when I saw that I was like amazed with the power of it. But at the same time, it was clear that without monitoring it without human fine tuning, monitoring, guarding it, it’s not a it’s not a smart move.
Beau Hamilton (16:50)
Yeah, yeah, you see glimpses of potential, but you have to get there. You know, you have to kind of keep refining, working out the kinks and finding a way to get there and maximize that potential.
Avi Kedmi (17:01)
There was this movie, I don’t know who was it, I think Adam Sandler with the basketball Netflix movie. And he said, you know, that NBA player, that draft player, he’s amazing, he plays well, he’s talented. And then Adam Sandler says, “persistent is talent”. That was in the movie. And I remember it because I think that, it’s talks about lot of product, products, especially when they’re young and young and new technologies. The, you measure their success a lot by the, by the speed of the iterations more than the value, right? This is one of things that we’ve done. We’ve launched it January 1st, and then we just, every two weeks, we listened to clients. We did what they asked for and we moved on. We listened to clients, we did that they wanted to move on. Now we have a lot of capabilities and more sophistication, but most of it after the first version that we invented is about clients driving towards where their usage is.
Beau Hamilton (17:52)
Hmm. Where do you see it going? You I know it’s, you talked about it’s hard to predict. I think even in the next few months, six months to a year, like that’s, it’s changing so fast, but you know, where, where do you see like SysAid going? And then on a, on a larger scale, where do you see the industry going over the next, you know, 12 months or so?
Avi Kedmi (18:13)
I’ll start with, I’ll start with the world and then the industry and then SysAid. I had dinner with a friend, good friend, very, you know, a person that I really appreciate and also, you know, is a founder at heart. I haven’t met him for six months. And I said, how are you? What are you doing? And he said, I’m okay. You know, I opened a new gig and I’m four months on it. And I said, the traditional, wow, did you raise money? What’s the idea? Do you need help? And he said, no, I didn’t, but I’m almost ready with the product. And I said, what do you mean? And he said, I bought three screens at home. have one OpenAI, one Anthropic and one Gemini. And I’m not a coder, he said, but I have the product ready. He said, I have the API, I have the documentation, I have the website, I have the… So he’s been working for four months, writing prompts to iterate and to get to the product that he needs, that the AI would output. Didn’t raise money, single person company.
Now, he didn’t go live, like most startup, maybe it will fail. That is a mind blowing approach. And I think he’s not alone. I think we’re going to have more and more people like that. So I think the world still does not understand fully the implication of what this powerful technology is and its impact on our life.
As an example, I think all of the teachers today, whether they know or not, all of the homework is done by AI. The teenagers are not going to sit down and write a paper. They’re going to write prompts that will bring the best paper. And by the way, different kids with different prompts will achieve different articles. So that’s on the level of the world. And it’s scary, but also powerful of how fast things will go out.
I think on the industry, as I said before, I think we’re on a trajectory to go to almost fully AI-contained environments that will have humans that will manage them, fine tune them.
And for SysAid, you know, our goal is to drive our solution, especially around the AI, to give a differentiated advantage. It’s, it’s, you’ve said it earlier, it’s like, this is a very competitive environment, also market, you know, the first week when I talked to analysts and my first week at the job, most of them said, you have no way to differentiate. And they’re right. It’s not easy. So where is SysAid going? We’re trying to make a lot of bold moves around building products that are GenAI based and to make it enough, fast enough and big enough. So eventually the differentiation would be just, it’s a different product versus what you can find out there.
Beau Hamilton (20:59)
Yeah. I think, well to your first, first point there on the, on the industry, just the way that AI kind of democratizes information and the fact that your, your, your friend was able to, kind of work through this product through just different chatbots and different prompts is amazing. I mean, it’s, and we just had a guest, Steve Yegge over at a Sourcegraph. He was, you know, these, he’s talking about their AI coding tool, you know, and just the fact that you can, you can do some high level coding, just with English, you know, basic conversational prompts. It’s pretty amazing.
And that, that just opens up the doors to, for so many different possibilities for someone like myself, who’s, you know, he’s really, I’m not a programmer by nature. I like, I know kind of surface level, a lot of the things, some of these, some of these areas, but like the fact that I could just sit down and just type in a prompt and develop my own app or whatever it might be is pretty incredible. And then you see like the Project Sora with film studios kind of being replaced, being able to generate your own kind of B-roll and different scenes just from, just from text. That’s exciting too.
I think you know, I think the next evolution, we’re starting to see talk about these AI agents, you know, which are essentially for listeners, that’s AI programs, chatbots that are essentially able to perform automated tasks for users, take over your mouse and click around your screen is just one kind of example we’ve seen, you know? We’ve seen Anthropic launch their agent tool. I believe it’s in beta still. And then OpenAI plans to launch theirs in January, as far as I know. Do you guys have any plans for these virtual agents at SysAid? I know, well, you did talk about…
Avi Kedmi (22:44)
Virtual agents we have already. Virtual agents we have already. But yes, we’re launching our beta in January around the aspect that you talked about. We have virtual agents, but I call it the next level of the virtual agents that they also do a lot of the task for you.
Beau Hamilton (23:02)
Yeah, what are some of the specific features or capabilities you can expect from them?
Avi Kedmi (23:07)
It’s interesting because we’re approaching it a bit differently. We believe that there are some preset things that they would be able to do. But also the power would be to have a workflow where the IT leader can define what tools he wants the AI to action on, test it, and also activate it when he feels that he trusts it enough.
So simple thing. I think I’ve shared it at the beginning. Let’s say you’re an IT person and you have a routine where in the morning you go over different systems and you check if there’s issues. Just, just for a second, let’s call it this one. Let’s say you have a system, you have your HR system, you go there and you say, who are employees that have left that still within closed their access, example, or you go to the, you know, the Azure LDAP and you say, show me all of the users that are, have been locked last night, right? Or show me all of the users that they’ve tried their password and before they were locked, they tried it a hundred times because maybe it’s security breach, right?
So you could speak to a machine. That’s what we’re launching in the beta and say, I would like a process that runs every morning and that does A, B, C, D, E, G, right? Write the code for me. Let me test it. Let me verify it. And also, and once he tests, and then it will be built for them. And then there’ll be processes that he will define that will start more and more taking the thing that was his routine. Now to build something that go through all of the laptops, checks that, checks what they installed. And at the same time goes to a different system that you do not have integration today. It’s hard to build all of it, right? So these are examples of things that you’ll see IT leaders starting to ramp up and build in a matter of hours to make things happen.
Beau Hamilton (24:57)
Yeah. No, I think that’s, that’s one of those things just with, just the chatbots you’re talking about earlier. It’s not like there’s going to be something that you adopt and go all in overnight on it’s something that you’re going to kind of find use cases over the weeks and months. And as this progresses and as the technology gets more advanced, right?
Avi Kedmi (25:16)
Also, we have to remember that GenAI has different use cases. If you are part of a system that risk is not a big deal, that’s one. To run a shell script over the laptop of an employee or some network device has a big meaning in terms of security. So, right? So we’re in a world where, you know, people are really careful what runs where and who’s taking over what, right? So I believe in this evolution, we have to go step by step. Sometimes when you jump too much, you will not get the trust of the people, right?
So you remember this, you remember this, this like image where it’s like, it’s the monkey that becomes a person that, you know, like the evolution of the world. So I think we’ll, we are like if today, ITSM or IT leader today, it’s a person, right? We are now, and the second phase was him on a hoverboard, like back from the future, okay? The agent one, the next phase, it’s him on a hoverboard with like 500 robots with him, right? And the phase after, could be, we’re not there, where it’s the robot on the hoverboard with millions of robots with him. But I think to try to jump to that area is a bit, in the world of IT, I think we’re still not there.
Beau Hamilton (26:50)
Well, I mean, you’ll get there. Like, like we said, it’s, it’s, it’s growing quickly. gotta, you gotta keep testing it and incorporating it here and there and seeing where it goes. And, I think, you know, you touched on the privacy and data security standpoint. That’s fundamental for any company working in this sector, you know, with, with data being core to your business. It really just makes you a prime target for, for bad actors, try to target you for that information, maybe rogue employees.
Can you talk about some of the measures you have in place to protect against potential security threats or vulnerabilities?
Avi Kedmi (27:22)
Related to AI or generally?
Beau Hamilton (27:24)
Well, just generally. I think when you deal with like, like you said, employee laptops and having agents control and work on locally like that, you know…
Avi Kedmi (27:34)
I think that every vendor today, every vendor that is providing a product to anyone has to assume he’s under attack 24/7. Just as, so and once you acknowledge that and live with that, right? Then you have to have like a few people that, that’s their job 24/7 to guard the systems. And also within these people, people that are focused on monitoring and alerting code that’s written by our developers that eventually translate to our product and all the other measures. So we invest a lot, not only in protocol, not only in certificates like SOC and ISO, but also in the systems we buy to monitor from the writing of the code to all of the laptops of the employees, etcetera. So I think we live in a world where security is something that’s becoming more and more something you just have to live with. I’ve been hacked. Sorry, people are trying to hack me on an hourly basis.
Beau Hamilton (28:46)
Hmm. Yeah, I can imagine sending, sending maybe messages to your employees saying, you know, hey, I’m stuck at a meeting, but I need you to wire me, you know, X amount of money. I can, I can imagine. I mean, it’s something that like, again, I kind of talked about the, covering the tech on Slashdot, but we, we cover I mean, there’s a ransomware attack, there’s there’s data breaches that affect millions, if not over a billion customers. It seems like that’s almost a daily basis nowadays. It’s really quite shocking.
That’s one, so that’s one challenge, you know, facing the IT service management industry is the data security aspects. But what are some other challenges that come to mind when you think of, you know, struggles and what to solve for with your product?
Avi Kedmi (29:32)
You know, I think the second aspect you see more and more is in the world of today, people expect integrations to be already there, plug and play. So when someone buys a product, you know, he expects that he goes to its marketplace, connects a few other systems, and then the data start flowing.
So like lately, we added Intune, is like a MDM mobile device monitoring product, it’s by Microsoft and it gather a lot of information on everything that’s happening on the network. So now we are able to provide to our clients when they have also Intune to just go to our marketplace, click add the token. And from that moment on, all of the information there will also be available seamlessly to the IT agents when they’re looking at assets and their information.
So I think this is struggle, but also an opportunity. The ecosystem within the world of today, where a lot of the system are already mature and have API that are solid, the ecosystem is expecting a lot more integrated experience versus go build a PS project.
Beau Hamilton (30:45)
Well, what, what factors do you look at to measure the impact of, of your product to make sure it’s, you know, having a positive effect for clients, you know, is it, is it customer satisfaction? Is it resolution time? Is it, maybe agent productivity statistics? Maybe all the above. I’m just curious to hear what your thoughts are on the key metrics for success.
Avi Kedmi (31:05)
There is a metric called MTTR for IT people, Mean Time To Resolve. And that’s the most measurable way to know the success of IT people. Does it take a few hours? Does it takes a day? And then there’s some others metrics like, you know, handoffs. Nobody wants to get help from someone that will move into someone else that will move into someone else. First contact resolution, which is like is this person that I contacted resolved it? Or then I had lot of exchanges until I resolved it? But above all, you measure it by the MTTR and that will also translate into productivity because if I need access to a system and then I need to wait two days to get the access, I lost two days of work. If my computer monitor is broken, now I’m waiting six hours, it means I didn’t work six hours.
Beau Hamilton (31:45)
Yeah, that’s, that’s a good point. I want to go kind of full circle here because you talked about the, know, work from, SysAid works with a wide range of organizations who work from small businesses to Fortune 500 companies across, I believe you said, 140 different countries. I think that’s quite impressive. So can you maybe provide some examples of how SysAid is tailoring their product to different industries or use cases?
Avi Kedmi (32:23)
Yep, for sure. For example, if you talk about service management, so we got quite a bit of clients in the industrial segment. So think about companies that has 50 factories or 100 factories across some place in the world. And each one of these factories has tens of tens of machines, whether it’s machines to saw or whether it’s machines to print chips, right? And now somewhere someone has a machine that stopped working or that machine connects through us through API and notifies it stopped working. Well, that machine now needs more paper and the paper is done.
These are all small service requests, but for a company like that, a machine not working for 30 minutes, that means a lot of time. Now, not always the people locally have also people with them to fix them and do everything for them. So sometimes they open a ticket and it goes to main headquarters to fix it or to order more things. So just imagine what does this mean? So this is an example of a service management use case that’s not pure play, just IT with like a company with laptops, right? It’s also, it’s also by providing a service to factories that will keep working, example.
I’ll give you another example of facilities use cases where we have companies that have worked with kids that are more on the spectrum and they have a lot of these places where they take care of them like most of the day. And now a lot of these places have issues where the just the bulb doesn’t work. They need a new one. Or the door is not opening well, it makes noise. So they use this service management system so people can notify anything they need help and then people come in and fix it for them or etcetera.
I was on purpose, not giving you a use case of my VPN is not working. My user is locked because that’s the trivial one. But you see service management across many use cases.
Beau Hamilton (34:29)
Yeah, those are great answers. I didn’t really think about all those different specific use cases, but I think listeners are gonna be getting a lot out of that perspective, customers, clients listening to this. I think we’ll enjoy that.
So I’m coming down to my last couple of questions, and I wanna ask maybe some thought leaders some questions, because you’ve been in the industry, you have a lot to share. You also talked about maybe there’s some young entrepreneurs just young leaders who are looking to maybe to jump into the AI space or have already jumped in, they’re not sure where to go next. What kind of advice do you have for them, for young entrepreneurs looking to start their own business and get into this space?
Avi Kedmi (35:13)
I think there’s a few tips. I would say generally to entrepreneurs. One is that there’s never a good timing to open a company. If you’re waiting to have more money, to have a more stability, it’s just that there’s never a good time. It’s just that the mindset you have to. I remember when I was 28 or 29 and I opened my company, I had a kid already. She was one years old. My wife was doing her academic progress and like no salary and I give up on my salary and I opened a company. But I could say, wait, when the kids will be older, I’ll have more time. Or when my wife will find a job. So there’s never a good timing. If you want to do something, just do it. So that’s one.
Second, I think would be especially around AI is there is an opportunity now across every industry. Basically, every product that was invented in the last 25 years, a technology, a software, is going to be reinvented by GenAI and will be 100x more powerful. So I think just means the amount of opportunities are enormous.
And with that, around AI, would say, a lot of times people are excited about something that they do that really with GenAI works great. I think it’s a connectivity of where you have a passion on and you have previous knowledge. So if someone, you know, has a good knowledge of finance systems and really know their pains, etcetera, then he combines it with GenAI and it’s powerful.
That’s some sort of the best ways things come into a success. But I think this is an era where entrepreneurs really, there’s no way someone would say, you know, I want to build something, but I don’t have an idea.
Beau Hamilton (37:12)
Yeah, no, that’s a great, that’s a great insight. Those are great insights. And it just makes me think of, you know, if you’re working for a company and it could be an accounting firm, could be, I mean, any construction, could be literally anything. And I feel like it’s, there’s opportunities to integrate these AI tools and automations. And, it’s just a matter of finding them and kind of finding the most value out of it, out of it. So keep, just keep grinding, keep working on it and keep innovating, you know?
And then also too, and then the thing you mentioned is like, yeah, there’s never a good time. You look at like the, a lot of, some of the most successful companies are kind of founded during economic downturns, right? It’s like…
Avi Kedmi (37:54)
Yeah. Uber, Airbnb. Yeah. By the way, it’s better timing on that because there’s less pressure on the entrepreneur to deliver very fast. As the world is still recovering. Yeah. I think that we were at a verge of something very big and also we’re not that far from a 15 years old entering even OpenAI and ask it to write a product or a code and then say, okay, also run it. It’s not done yet, but what’s the gap, right? Just also run it. And then you have people inventing things and they’ll already be live.
Beau Hamilton (38:27)
Yeah. Yeah. Hey, well that’s, that’s great. And I think that’s a, that’s a perfect way to kind of wrap up this interview. I think there’s a lot of insights here and I, I’m excited to, to see how this turns out. And, also I think there’s a lot of like good, just shareable clips that we can, that people can find value out of without necessarily the full context here. So I’m excited. And, for those listening, we’re can, where can you send them to learn more about SysAid aid and get in touch with you and your team?
Avi Kedmi (38:56)
I would say sysaid.com. Usually it’s a great place to find about our products, our open positions and more. I’m accessible to anyone in the world that want to ask questions, etcetera. I’m on LinkedIn. I don’t miss a message. I know that 90% of them are spam, but I don’t miss a message that’s relevant from a real person that’s really interested, not only selling. So I think these are, these are the best places.
Beau Hamilton (39:19)
Perfect. All right. Well, that’s Avi Kedmi. Thank you so much for taking the time out of your day to talk with us about SysAid and AI. Appreciate it.
Avi Kedmi (39:28)
Thank you very much.
Beau Hamilton (39:30)
Thank you all for listening to the SourceForge Podcast. I’m your host, Beau Hamilton. Make sure to subscribe to stay up to date with all of our upcoming B2B software related podcasts. I will talk to you in the next one.