Innovation in Engineering: How Daniel Bin Zhang's IPS is Changing the Game

Jake Aaron Villarreal: Welcome to our podcast, From the Ground Up, where we interview startup founders exploring their journeys, their success, challenges, and lessons learned. We hope you be inspired in discovering what it takes to build a thriving startup.

IPS is revolutionizing engineering and digital transformation in sectors like oil, gas, chemicals, power, all with artificial intelligence. Today we'll explore how they're benefiting plant owners, operators of large engineering firms, and the latter in digitizing the engineering process, saving organizations vast amounts of time and money. With Daniel, Jen has over 30 years of experience in his career, with a wealth of experience cultivating from working at Dow Corning uh and in Asia Pacific. And his tenure with top tier engineering firms has honed his experience in capital projects, operational excellence, and industry insights. Since founding IPS, Daniel has been a leader and innovator in digital transformation for the process industry, leading the changes of data transformation with AI, and has helped multiple large global clients in their digital transformation journey. So Daniel, uh before we dive into your company and get all the details there, uh where are you joining us from today?

Daniel Bin Zhang: Yeah, actually I'm calling from Vancouver, Canada. Actually it turns to a very bright day today. You know Vancouver typically is a raining winter, but it's a good day to connect and talk.

Jake Aaron Villarreal: Great. Are you from there originally?

Daniel Bin Zhang: No, actually um I'm actually born in China. I grew up in China, and I went uh university there. And about 25 years ago I came to Canada, I did my master here, and I stayed on and went to different consulting company. Then I went back to Asia for... continue working there for 10 years.

Jake Aaron Villarreal: Great. So you know, this show is really about the entrepreneur experience and going behind the scenes of what it's like to, to build a company. But you had a lot of experience on the corporate side during your upbringing. What helped shape you with the mindset of one day wanting to be an entrepreneur?

Daniel Bin Zhang: Actually um quite interesting um because um yeah I was born in Xinjiang, uh far west east region of China. Actually my parents almost like immigrant to that region. Uh they actually uh built the first railway to that region uh almost like 60 years ago. So, so they were kind of pioneer going to that region. My dad told me when they went to the city at the first couple months they... even there no place to, to stay. So they were actually literally uh stay in the camp for, on t-, for a few, almost a year. So they were like their 20s, they left their family, they went there, they stayed for 30 years all their career. So it's uh kind of interesting. My dad always said, "Co-, we had nothing. We just went there, build the first railway in the desert almost." I think that's a little bit adventurous. Uh so we grew up very independently.

Um and actually had a company when I was 20 years old. When I just graduate from school, uh I actually started a company with my high school uh classmate. Uh we were actually um brought the Siemens first heat pump uh to the China. We sold it actually in two years, grew company from two of us to almost 25 people. And that's in 1993 to 1995. That's almost the first money I made. And I thought "okay, that time looking for the Western management uh and how basically that's the reason I came to Canada, looking at, to learn, grew up here to learn how things running in the Western word." That's obviously long time ago.

Jake Aaron Villarreal: Yeah that's great. What was the product you, you, you started again with?

Daniel Bin Zhang: Actually that time uh you know, the heat meters. Basically in northern China is, is all winter time they have huge uh heat supply system. And basically people, that time the government is charging people per square meter winter, right? You per square meter, basically there no measurement. And the Siemens had an a heat measurement device which they can actually meter, it's a meter to actually measure how much heat supplied for individual companies or, or families so they can have a measurement to charge how much you... It's like a charge your water, but the, the way they matter is heat. That's pretty new technology for China. Um and we were the first uh small company actually brought that into the region because this winter is very cold. And yeah, was quite interesting because obviously that time China still, if you are you know university student and you can speak English, that's pretty much you can't have you know connection with foreign companies, actually being able to do it. Now obvious those things been changed a lot.

Jake Aaron Villarreal: Yeah, no doubt. That's great. So heat measurement makes it interesting. Um so great, so that was kind of your real first entry into being an entrepreneur, which is at a young age is really I think a good time to take those risks and take those chances. Um we're going to talk a little bit about um the company that you started here. Uh you worked for Dow and you worked in Corporate America for a while. What was it that you saw, what inspired you to leave that to start your current company today?

Daniel Bin Zhang: Actually uh there's two things. Uh one thing is, you see whole my career is in large corporate after my first uh small company I moved here. So I start working mostly for a large corporate and as my role and responsibility grow, I at one time managed quite a lot of capital investment in Asia Pacific building different factories. And one thing I always feel there are just so much waste in the work we have done. We always repetitively use the engineering information to build new plant, to be expanding it. Uh that's one thing. And another thing is actually we have invested so much in the past and some of the plan we build never operate. It's not because technically they are not correct actually, because when they build the acttion market is gone. How we can more efficiently invest building engineering much more efficiently and also improving efficiency in operation is critical the time. You know as industry move forward, in the past in the old time you, you 10 years to build factory is okay because markets response is slow. But now require you actually building three years, otherwise your competitor would take the market, right? That actually is the driver. Always see what we can do for the industry.

And uh actually one the event is uh when I watch that document com about AlphaGo you know, that the change, the, the machine beat the people to play the Go game. I looking at that say this is just the same thinking behind how we do engineering. What we can do actually to use that technology basically... Actually the five years ago I was more looking at generative design space from engineering but obvious company take a different tool now. Direction now looking from the data, data extraction, data uh structuring and, and digit the work process. But I think ultimately we're still looking at the end of day, with the data we have to move into the generative design as well.

Jake Aaron Villarreal: So when we talk about engineering in, in your case, you know, for a lot of the guests that have been on the show, they're building software applications and they're driving um you know solutions around AI and companies that are using their technologies. When we talk about engineering with your company, you're using software technology, but your customers actually have physical plants correct, and piping and joins and different components. As they build a manufacturing plant or any type of plant or processor, um there's a lot of decisions that have to be made, and there's a lot of ways that you could help streamline the process, maybe save them time, save them money through AI and technology that you're building. Is that correct?

Daniel Bin Zhang: That's correct. There are many different way looking at how this, how the physical side being managed, operate right. One of the key components of being efficiently operate a plant, refiner or chemical plant or food, food plant in, right, is looking at information right. People... how people can be efficiently find information, exchange information, create new information. Everything is about engineer data. There are lots of company focus, fusing on operational data. Operational data is like IoT right, those are operational data. But the large amount data actually is related to engineer data.

So we focus really looking at engineering data actually when we start five years ago. It's very niche, not so many company looking at. You will see a h- hundreds of IoT company, hundreds of data analytical company looking at a maintenance data from analytical way. We looking at engineering, no one touch it because I know in my old uh plan was managing there are millions page of, of engineering data on the PDF, on the Excel, on the Word document. People still crouching on a Word document even to find the data take some hours. So that's where I looking at see okay, how we can just take that chunk to start with, right.

I was in the, I was looking at Microsoft. Look uh the way of they looking at using AI to uh to improve uh the efficiency of an organization, there are three part, part of that one. First thing is I called foundational productivity. Those are things the day-to-day people, how many people are working trying to find things, trying to exchange data, compare things. The second part is trans- uh transform, forming. That's is where you're looking at digital work proc-. The, the really, really the last stage is the Generative, which we're going to move as well, is where you're actually looking at the generate uh the thinking process, how you design all that. So there are different piece of that transformation.

Even just to get foundational right is a huge, huge need in the market. As more and more companies start building digital twins, our client came to us that they wanted to build digital twin. Beautiful 3D model, empty, there nothing in there because there are millions of pages document they want to get information out. And the structure that, the casing is structure it, because its industry is very famous on, on variations, non-standard, inconsistency. See how to solve that as a foundational work is important. I think we address that, but we certainly now is moving into we call AI workflow, which is digital work process to looking at how data exchanged, how data integrated, how data actually when it, you structure it, and that actually paved the way to the next st- stage of generating. Because you don't have structur data, how machine learn to generate, right? So I think that's the we call the road map for the future.

Jake Aaron Villarreal: What's a digital twin?

Daniel Bin Zhang: Digital twin basically is an... think about it's a twin right. So you have a physical asset is a building, a factory sitting there as the real. Then you build a twin which in a computer environment which is a 3D environment, everything is a mirror of the physical asset. But differences the physical asset has let's say they have oil, they have chemical running it, a twin has data running it right. The critical thing is it's a beautiful picture, but without data then you cannot really do much about it. It's just a good picture right. So data is the foundation of the digital twin.

Jake Aaron Villarreal: So you could take a factory that's operating and create a digital twin, put in all the data that's, you've been gathering from how that, that's operating, and be able to utilize AI that's going to tell you how to more efficiently operate that factory or maybe make changes to it that's going to increase productivity. Is that kind of the how you're, the benefits you're providing to companies?

Daniel Bin Zhang: Yeah there are multiple benefit in the dist- twin. The first foundation of uh is actually is the centralized data which people can easily find them, looking at them. Because they think about the large factory, the amount of data is significant high, to be efficiently using it and voiding in the, in especially oil gas chemical industry, safety is very important. If you got data run, you have a conflict of data is the, is the risk for the operation right. So that's, that's the way to do it. And then you can look at the data how... because factory will never... none of the factory will build once and stay like that. They always keep upgrading, changing, maintenance. There are lots of data on the day-to-day uh site for engineering maintenance work. That's where we looking at how we can efficiently using data. Even just to get the data efficiently into the digital twin is the huge challenge for the most organization actually. We just did a survey to looking at digital transformation, especially because the digital asset or digital t- initiative, the first thing they challenge is how I can get the data out of from the millions and millions of documents. The second thing actually is extremely costly for them to do it. Yeah right. So how we can reduce that cost to actually we call us enabler, to enable you into catch the first step. As the strains we have buil- over the years as the you know, the markets been all phenomenal, just this actually COVID has, has really pushed that. For, for company understand they have to have remote access. The digital twin is a way for them to have to work at any place, any location to be able to monitor, looking at, even control the physical asset.

Jake Aaron Villarreal: That's great. You know, you hear of these companies building AI, but some of it is they're building it hoping to find their target audience. You've got the target audience. You've got real companies that have been operating for years. Um but then the transformation of taking the data, pulling it into an AI model that then you can show how it's going to help them be a better company or operate better is uh I think you know that's, that's the, that's the goal of most companies. So I think what you're creating is, is, is incredible. Um you know, just a side story, you know, when I came out of college I, I wanted to go travel. And I had friends that traveled the world for a year at a time after working for the summer. And they come back and I, I asked them, you know they came out of UCLA, I said "What, what are you doing to make money? Because I've got no money coming out of college, I want to go travel." And so they said "You know, you go work for this company in California where um you haul tomatoes and you go up and down the highway all day long and you, you drive an 18-wheeler truck and you know it's 80,000 pounds of tomatoes and you live on a tomato plant and you don't spend any money. You do that for three months, you make $15,000" (this is when long time ago right). And so I did it. And I went and surfed Central America for a year, came back and went you know, around the world, came back, it was all from that company.

But it was a tomato plant, and that tomato plant was built by eight growers of tomatoes, but they'd never built a plant before. And it was one leader uh in that group that said "we'll build this as a collective." Um and then he went, after they built that, about 5 years later and he built another plant on his own. But he took all the learnings that he did in the first plant of what worked and what didn't work, and he became a very wealthy man. He turned that into a $700 million company. And they produce more tomato sauce than Italy today, based out of California. Okay, but the interesting part about that was is that he actually would walk the plant. And he was very manual, so he understood every single component of that f- factory right, with the data that it took. And then to take that and to improve it you know, he was way ahead of his time then. But I could see how if you have all this data and you don't know how to improve your operation, but now you've got AI or you've got a technology company like yours that could bring that to the owners or to someone else who wants to build something similar. You've got data that's very valuable that can help optimize your operation and quite frankly just make you more efficient and more profitable.

So those are the things that I think are really interesting about what you're creating. And I know I'm not hitting everything that you're doing for these companies. Generative AI I'm sure is there where people can punch in some questions and get answers to the data once they're in your platform with their, with your systems. But um you know, the technology itself has come a long ways. How big of a team have you built to support these global companies? And, and, and are you a global company yourself?

Daniel Bin Zhang: Yeah, actually quite. Because uh my, my personal experience you know, I've been traveling around working at different location globally. And especially my uh my before I start company, I've been actually stationed in Asia, lived in Shanghai, Tokyo for 10 years managing very diverse team globally. So I actually start company as almost a global company from day one. Um so I'm very used to using uh different resource globally uh based on my past experience. The company at this point, we actually have uh three offices. Uh the, the obviously our main office is based in Canada. But we have an office in India, that's basic our software development support center. We actually have quite a large uh office in, in Cebu, Philippines, that's basically our engineering team. Uh they do both uh design of the product, testing product process and user. And also we actually also provide digital service based on our AI to, you know... AI wouldn't get you 100%. If anyone come to their customers say their AI is perfect 100%, something is not right. So, so we actually also provide last mile service to, to our large client globally. Uh so in and out I think including contract employee we probably have 120 right now. We're going, going to open uh our uh Japan office uh in January, February time. We're in the process open it with our large client in, in Japan, we partner Mitsubishi in Japan.

So our customers also very global, and we have North American couple of large client here. And we have large client in, in Europe. Uh the, the couple biggest oil gas and chemical company there. Uh in Southeast Asia we have a large state-owned company, we have been providing digital transformation uh with, for them. I just mentioned we, we partner with Mitsubishi, the Japan market just started. Um I think we, we're going to have the first two projects start in January. And it's just uh it's just everywhere we go we just see, see opportunities, we just say the company asking them those challenges uh they are, are facing today. Yeah, we're just the, yeah we're a global company from day one and we will stay that, we'll grow. I think uh you know this is the time basically everywhere dist- transmission I think just started.

Jake Aaron Villarreal: Yeah that's great. Um well you're global, you've got lot, lot of people working for the company. Uh it sounds like a ton of demand for your service and for in general um for the industry. What are some of the challenges you face today in the industry?

Daniel Bin Zhang: Um I think uh obviously for any company, talent is always the biggest challenge in reality. The company is scaling up, is growing, is scaling up. For sure we need to build uh the processes, uh the systems to mean to support the company to scale up. But at the end of the, the company needs to deliver a product and service meet our customers' expectations. Whether it's be efficiency, whether it's been productivity, whether it's been cost, whatever that is. To be able to deliver, you have to have the right people to be able to building uh expanding your team. Uh not uh a number but quality, having the right leadership team to, to be aligned. Uh whether it's you know, you know value, v- vision, culture. And have the people who has the capability to communicate tech- technically they're capable, and also all the software skills coming with nowadays communication. Especially our team is very global right, it's a lot of remote uh collaboration. So I think yes, at the end of the day it's better you get right people and right people to move things and execute and deliver.

Jake Aaron Villarreal: You know, it's not always the leader uh that makes the company successful. It's the technology, but the technology is built by employees. So talent is absolutely imperative you get it right. What do you do to make sure you filter through to get the right people for your company and your culture?

Daniel Bin Zhang: I think uh obviously uh there are traditional way you know. I think there are traditional way you have to look at from interview. You have to look at you know uh we do actually work with um different uh HR consultant and companies to let them help, because company has grown so quick. We start in 2023 has 20 people, now six times bigger right? Yeah, yeah. We, we have to uh uh you know uh uh you know grow internally, but we also have to rely on some of the partners to help us to grow right, and to establish uh right process. And the second thing is um you know I think one thing for us to how we be build leadership and the mid, mid-level, the middle level management team, which they have tremendous experience in hiring uh maintain the, the organization, manage performance. I think that layer I think for, for our organization actually, mid-level for sure. Your senior leadership building things, visions, all the things you need, get company into the direction, but middle level uh management team actually is critical for company grow. I think that's our really focus, we trying to bring the right people in.

And, and also uh you know uh this is, this is challenge for any company. So as, as company like our size and our growth right, I think there also have a try and fail uh right. And we have to get people coming, you know, you do all the things you can do looking at you know, trying to figure out the best people, but other thing you have to find "try and fail." I think we are more open to try and fail as well basically. I think that's critical right, whether people are suitable for... people are, lots of people are great people, first of all whether they're suitable for this of environment, extremely fast paced right. A lots of stress and challenge and uh but also looking at people who actually whether um the, their skillset is fitting to you know the skillset. Again, we're quite innovation company right. So I think those things are critical.

Jake Aaron Villarreal: That's great. Yeah, it's a, it's a... there's no silver bullet for every company. Every company is a little different, the cultures are different, their size and location. Um how do you differentiate I-, IPS in the market from other competitors out there today?

Daniel Bin Zhang: I think uh one other cas- thing is uh I think uh we start early on this journey uh as uh as a few things. Uh five years ago when I start company actually um in this field actually you looking around uh you can't even find company doing what they do. Uh funny thing I tell you st- this is the real story how I caught the find of my co-founder. Uh our co-founder, our CTO, he original from ac- mc background uh used to be a professor from Indian university. He moved in Canada and he was teaching and I connected with the friend. I, I told him what I want to do. He look and says "This should have lots of people thought about it." So what he did because his academic background, he actually did the research to trying to find the research on it. Only found two paper, only two paper. So he was like "Wow, this is interesting, no one has actually looked at this direction at all." So actually he hooked on it because of that. And uh you know and also at the beginning he thought it be easy, then he started really trying to find there l- different challenge. With other you know AI apply in, in other image recognition, other stuff, it's very different domain. That actually actually bond us together start companying together.

So we are very early and we developed certain technology today we're still very much ahead of other companies. Especially in the graphic you know, we're dealing with engineer joins. Those are not, not cast dogs, cars on the road, they have complexity not only recognize them and understand the relationship all those objectives and also data around it. So we start early, we have again the years of fail and try and fail and you know taking the new technology where we ahead of many other competitors. So our lot our competitors stay at I call text level, we more looking at graphic and relationship, that's where we strong at.

Jake Aaron Villarreal: How big of a market is this for you?

Daniel Bin Zhang: This market actually quite interesting too. You know when I start companying I was looking at um the, from an engineering perspective. So I, I tell you what I did at the beginning, I add all the public data looking at uh all the engineering work for oil gas chemical. Just for oil gas chemical, not looking at even power, everything. The cap investment is about 200 billion a year. So that's actually quite big right? And I said that time actually five years ago looking at digital twin market in oil gas, they're talking about 40 billion a year. And I read the paper last week you know what the number is? You're talking about trillion.

Jake Aaron Villarreal: Wow, yeah.

Daniel Bin Zhang: Traing. So this is obviously market has blowned so much because in a way because the COVID as well uh you know the digital turn concept has been around almost 15 years. And the five years I go to a client, lots of client, even a large client first time heard about it. Now you go to company you don't need to talk about this thing. They know it actually, they know what their pinpoint, I tell them what's the solution they're happy to see there is a solution. So that's how much things has changed in five years. And for sure in next five years this will be even more looking at you know oppos- because the ChatGP- other new uh technology in the market now right. So we're looking at also how we can utilize the lat- is the greatest technology to improve us and providing more value to our customers.

Jake Aaron Villarreal: How do you get your foot in the door with new customers?

Daniel Bin Zhang: Well um I think in a way I'm lucky, u- because my experience in the past with a huge uh network of uh of company is a great company in the world building. I do have a lot of personal relationship in that industry with deep understanding. And also I think one of cas- thing is we speaks the language uh industry can understand. When you go back to the company, tell them the challenge that which I have experience, my past experience, they can leak right? They know what it is, they understand what it is. Um so I think that giv us a lot of opportunity. So when we start first try our products, actually one of the, one of the largest global engineer comp actually waiting to try. And uh you know since then we obviously take a much quicker uh you know expansion. Is that, I think that's I'm a little bit lucky in that way. Everyone has that luxury to be able to do it so...

Jake Aaron Villarreal: Are you founder-led in terms of getting your foot in the door and, and, and getting new clients? Or do you have, is there like a marketing strategy that you felt really worked for you that could share with the listeners?

Daniel Bin Zhang: I think we are trans- trans- uh I think we are in, in, in the process to transaction from, and from the le- organization from, and sales, marketing to a real marketing driven, sales driven um. As, as you, you heard we actually are most of customers are large uh corporates and we do actually continue to, to discovery. And we call the nigr- basically we divide our, our market into different segments which including owner operating company which the owner of those refineries chemic pl-s, and engineer company, and actually we see a new industry called digital transformation solution and service company. That's almost like most of the our partners. We, we divide by size and we're looking at it kind of like a hit map and understand market now and see okay well instead of everything key account management, actually we see a lot of we call the mid market, the mid size oil gas chemical company is actually ring- very move very fast on transmission. Sometimes much faster than large organization. So that company obvious we don't have that many people to all have connections. We're actually moving into a more marketing driven approach. And we see in the last um six months we see a peak of that. We really next year is really focusing how we can providing that and move into a called general market, which is get into the smaller mid size engineering company. And you, you see the you know markets on globally the, the engineering uh company to serve this industry close to 60,000 engineering...

Jake Aaron Villarreal: Wow. 60,000. If you take a 50,000 sell to a company, that's a pretty good number. Wow, that's great. That's really cool. Um wow, that's impressive. Um I guess as you look into 2024, sounds like you get a lot of demand. What's on the road map for IPS?

Daniel Bin Zhang: I think there are obviously scale, scale up is uh is the most priority we have. We have build you know products and we're trying to basically really move into a as, as I said general market into a platform type of company. We are selling as more s- to a large company right now, but we are trying to move into a general platform so small medium company can actually access and do. That's one the key change we want to achieve next year. Um the, the second thing actually we can, we need to really need to continue to innovate because the CHTP is a large language model. We seem, we already start some work this year. We see very significant improvement from our own technology. We're extremely um happy to see the change this year and see how we can bring more value to our customers. And uh then uh on, on a little bit further looking we, we do want to start looking at generative design basically, because we have lots of data structure data right, that's the advantage we have. And we already start testing some of just the from converting join to actually generating design.

Jake Aaron Villarreal: So as a company looks like a lot of growth and utilizing AI even further. Um God I can't wait to see how things go for you in the future here. I uh love to come get you back on the show or just hear the progress. I know there's a lot happening in Japan right now. I know we you know we help companies grow and scale all over the world, so we're hearing trends, we're seeing hiring you know at levels that you don't read about in the pap- but you're seeing it in the trenches of companies that are scaling up in you know different parts of Europe and Asia. And we're excited to listen and see what else is happening with companies using AI. Sure, um if companies wanted to find you or find your company IPS, where would they go?

Daniel Bin Zhang: So I think we actually social media, we actually focus on LinkedIn.

Jake Aaron Villarreal: Yeah.

Daniel Bin Zhang: LinkedIn is the professional industry type of you know market media right. So I think uh they certainly can find us. And you, you know, you can send me email if you interested to, to do...

Jake Aaron Villarreal: All right.

Daniel Bin Zhang: Um yeah I'm always happy to, to looking at the people not only a customer, but more important AI community. Because there are so, the, the, the way I start company actually I'm not looking at engineer, I looking at other industry what they do with AI and borrow the ideas to this industry and how we grow that. I think that's continuous journey. I just came back from Japan uh with the mission with uh Canadian government uh treat mission to Japan. One of things we met lots of Japanese company which already been working with, but the most interesting thing is actually the, the, the team Canada who has lots of other AI and companies doing different things in different industry. When you meet together was looking at what they do in finance, in, in, in alu- industry. I'm looking at we can use that in our field. I think that's the great thing. I, I think what you've been doing in this community to put AI company together to, to, to look at different AI in different industry how we do things, I think it's, it's very valuable for the community actually. I thank you for doing that.

Jake Aaron Villarreal: Yeah absolutely. It's, it's moving at such a fast pace, it's fascinating to hear in the trenches what people are doing and, and what value they're bringing to companies. Um well I want to thank you so much for jumping on here Daniel. I know that there is a huge opportunity in front of you in the future. And for those that are listening that may have an interest in wanting to work for you at some point, where are you hiring, what type of roles are you hiring for? They might want to just reach out and connect with you directly.

Daniel Bin Zhang: Sure. Yes, please do. Yes reach offs on, on LinkedIn uh just looking at Intelligent Project Solutions and then we're there. We actually have lots of actually opening next year, the, the company is growing uh significantly fast.

Jake Aaron Villarreal: Great, cool. Well thanks for joining. Appreciate you Daniel coming on, your courage for sharing your story. And for all the listeners listening, means the world to me that you've chosen your time to spend with us. I'm your host Jake Aaron Villarreal and here with you uh today, but we'll be next uh week with you again on our next episode. Until then enjoy and take care.

Daniel Bin Zhang: Thank you.

Jake Aaron Villarreal: Before we wrap up I want to give a big shout out to all the entrepreneurs that have joined to make this podcast possible. And for all the listeners for listening, it means the world to me that you chose to spend your time with us today. I'm your host Jake Aaron Villarreal signing off for now, we can't wait to connect with you all soon on the next episode. Take care.  

This show is sponsored by Match Relevant, a company that helps venture startups find the best people in the market. And they do it in three simple steps. First, they sit down with founders to understand their story. Second, they tell their story into multiple candidate channels. And third, they schedule interviews within 48 hours. Find us at matchrelevant.com to learn more about how we do it.  

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