The Future of Estimating

Podcast Transcript

Steven Rossi:

Hello there, and welcome to the Construction Revolution Podcast. My name is Steven Rossi, and here on the show, we explore the latest trends, technologies, people, and organizations that are revolutionizing or disrupting the construction industry and are changing what the industry will look like tomorrow. Today, we’re thrilled to have Melvin Newman on the show. Melvin is the cofounder, president, and CTO at PataBid. Melvin has over 15 years of experience as an estimator and project manager. He also has expertise in many key aspects of construction and prefabrication in the mechanical, electrical, and general contracting industries.

PataBid is a construction bidding platform that is changing the way contractors approach the bidding process by using cutting-edge technologies such as artificial intelligence and machine learning. So if you’re a contractor looking to stay ahead of the curve in the construction industry, you won’t want to miss this episode. Let’s dive in. Hi, Melvin. Thanks for joining us on the podcast today. How are you doing?

Melvin Newman:

Great. It’s snowing outside here, so wonderful way to kick off spring and almost summer.

Steven Rossi:

Oh, yeah. Well, we got to have a snowstorm in April, right?

Melvin Newman:

Yup. Every time.

Steven Rossi:

Yeah. Before we get into spring, you got to have another snowstorm.

Melvin Newman:

Make a point of it. Yup.

Steven Rossi:

Yeah. Well, hopefully, snow doesn’t stay too long.

Melvin Newman:

It’s actually sitting on the grass out there. I’m looking out the window right now. It’s not the greatest welcome.

Steven Rossi:

Okay. Yeah. We saw snow yesterday, but thankfully it didn’t stay.

Melvin Newman:

You guys had a wicked ice storm there a couple of weeks ago, right?

Steven Rossi:

We did. Yeah. That was fun. I still have a large tree branch sitting on my power lines in the backyard.

Melvin Newman:

That’s not good.

Steven Rossi:

Waiting for that to get rid of.

Melvin Newman:

Yeah. But you obviously have power, so that’s a good start.

Steven Rossi:

We do have power. Yeah.

Melvin Newman:

Or you’re pedaling really hard underneath the desk there on your little pedal generator.

Steven Rossi:

Yeah. No. Thankfully, it didn’t take the power lines down yet, but just sitting away.

Melvin Newman:

It’s not comforting. That’s for sure.

Steven Rossi:

No, definitely not. Okay. Yeah. Again, thanks for joining us today. I’m excited to learn some more about you and also about PataBid as well. So just get us started. Could you tell us how you got involved in the construction industry to begin with?

Melvin Newman:

Yeah. Absolutely. So construction is a bit of a family business for me. My dad was a mechanical engineer, and so I grew up in and around that. When I was a teenager, we moved out to Nova Scotia to do one of Canada’s first design-build water treatment plants. It was a project my dad was on. I was 13, and he would bring home the drawings to work on in the evening. So spent a lot of time over the table just curious, learning how these things worked, that sort of thing.

And then when I was in high school, I was all excited about tech. Looked at comp sci, computer engineering, that sort of thing. And then the dot-com bubble happened in 2000, and everything imploded, and I came home from high school one day and I’m like, “Dad, I don’t know what to do here.” And he looks at me, he’s like, “Well, they’ll always need to build things.” So went through for mechanical engineering myself at Algonquin College and then started my career in Ottawa with Black & McDonald, a construction company there, and within a number of weeks, really, realized, “Wow, the construction industry is…”

I couldn’t believe how many faxes were still happening. I’m like, “What are we doing faxing things? This is nuts.” And my manager there was an incredibly forward-looking gentleman, and he basically looked at me and said, “You think you can do better?” And I’m like, “Well, I’m not some crazy genius, but I got to be honest. There’s a lot better out there.” And he literally said, “Go do it.” And he basically gave a blank check and then promptly hired two other guys that I had graduated with and then a guy who graduated the year before us, and basically looked at us and said, “Go fix this.” Start doing virtual design construction before that was even a thing.

So he got us total robotics layout stations. He got us one of the first Trimble 3D scanners. This was way back still in the early to mid-2000s. And so, that was really where I got started in construction. And right out of the gate, just due to an absolutely fantastic manager there, was really given construction tech in the lifeblood of it. So yeah, that’s kind of my history, and then moved to some different companies and across Canada to see what else was happening in construction, get a feel for different sort of things.

And it’s been really fascinating, because in every one of those steps, construction tech has been the core of what I’m about, what we’re doing. And then, yeah, finally, I realized, “Wow, there’s some major place for innovation here.” And started a company with my business partner from out East. He’s still in Ottawa, actually. Well, Smiths Falls. And we went to school together, and started doing stuff with AI just to automate my own job. I was working for some companies and had a lot of different tasks to do and realized that AI provided a really unique way of doing this.

And when I say AI, I mean true machine learning AI, not just some cool rules around databases and that kind of stuff, which you can do some cool stuff with, but that’s more what I call automation. But when looking at things like public procurement and trying to source opportunities to bid on, there is such a fantastic mess in that whole situation. It’s a disaster. And machine learning enables a way to filter that at a much more intellectual level, if you will, because it has… There’s a lot of limitations on machine learning AI. Everyone looks at ChatGPT like it’s the next greatest thing.

It’s an evolutionary step, and they’ve done some profound things on the technical side for how to train massive language models. But the reality is, they’re not perfect, but they bring a certain level of intuition into it that enables us to automate a whole new realm of tasks. So yeah, that, in a nutshell, is where I came from. You’ll notice, I apologize in advance, I can get very animated and excited about this, because the tech, everything is moving at such an awesome rate right now, and construction is finally getting into the middle of it. We still have a lot of hurdles to overcome, but it’s happening in construction now.

Steven Rossi:

Yeah. No, for sure. No need to apologize. It’s great, but we love having people who are passionate.

Melvin Newman:

I tend to nerd out sometimes on this stuff. Feel free to say, “Okay. Back it off, man. You’re going down the rabbit hole.”

Steven Rossi:

Yeah. No. No. No, not at all.

Melvin Newman:

Yeah.

Steven Rossi:

It’s interesting. And, I mean, I think everyone, especially tech companies in construction, are well aware of how old school the industry is. And thankfully, we are definitely seeing that shift now, thanks to companies like you guys and also with us in different aspects of the industry.

Melvin Newman:

100%.

Steven Rossi:

Uh-huh.

Melvin Newman:

Yup.

Steven Rossi:

Yeah. We still got a ways to go to catch up.

Melvin Newman:

We do. We 100% do have a ways to go. And full transparency, I think some of that has to take place in the education system now. We really need to start to bring this technology drive into more of the trade schools, because the reality of what’s happening right now is our trade schools, Algonquin, SAIT, NAIT, all of these schools, are producing very excellent electricians, very excellent plumbers, carpenters. They can go and do these tasks very well, and we desperately need that in our society right now. But we’re not giving them the foundation they need to step into the business side of this.

So a lot of the clients we’re actually running into at PataBid are still, the only thing they know is pen and paper, because that’s all they were taught in the schools. And they have a wickedly vertical learning curve when they go and they do their apprenticeship. They get their master electrician ticket. They get their plumbings, Red Seals, and all of this kind of stuff, once they’re done, their first five to 10 years in the trade, and then a lot of them are looking at, “Okay. What’s the next step? Okay. Let me go start my own company.”

But we have nothing to prepare them for that. And there is so much more to the company side of this that they are only at the highest levels touched on in their education. It’s not even really hinted at the number of guys that we run into who are like, “Yeah, I started my own company and I didn’t know what an estimate was. I didn’t know what this was that I have to produce now to survive.” And it is really, really tough for them.

So, I mean, there are some great training organizations. We’ve got a partner, Suderman, out of Calgary here, and they are an excellent training organization, but they’re hyper-focused on electrical. We haven’t found anything like that in the mechanical plumbing side of things or in the carpentry side of things. So yeah, I realize I’m kind of going through a lot of what’s happening in the industry, but this is largely based on what we’re actually seeing in PataBid with our clients. And I think the next revolution of technology to prepare the industry needs to start to happen at the education level. We need to start to drive it in there.

Steven Rossi:

Yeah, for sure. No, I think that’s a great point. I mean, that’s exactly what we’re here to talk about, is how we revolutionize the construction industry, right?

Melvin Newman:

Yes. Absolutely.

Steven Rossi:

So we’ve got to start somewhere, and starting, absolutely, with education at the base level is very-

Melvin Newman:

And it is starting to happen. Last year, I’ve been heavily involved with SAIT, which is the Southern Alberta Institute of Technology here, and they’ve started to capture that vision. They really have. They’re engaging with industry directly on, “Okay. What technologies do we have to teach our students?” But it hasn’t made it, from what I’ve seen, into their trade school yet. It’s happening at their mechanical engineering technologist level, at their civil technologist level.

But we need to start to drive that, especially because on-site now, tradesmen are being asked to drive this technology because it’s starting to integrate. We’ve all seen the Hewlett-Packard. Have you seen the site printer there that they’ve released?

Steven Rossi:

Yeah.

Melvin Newman:

Yeah. We’ve seen that. We’ve seen the Trimble total robotics stations, and now they’ve mounted the thing on the Boston Dynamics dog, and it’s like, “Okay. Technology is starting to invade the site and we need our tradespeople to understand how that works. Maybe not in-depth, but how to at least use it.”

Steven Rossi:

Yeah, absolutely.

Melvin Newman:

Absolutely. It’s a major facet of construction right now.

Steven Rossi:

So getting back to PataBid, can you tell us the story of how PataBid was founded and what you guys do?

Melvin Newman:

So PataBid is, basically, it started out, it was founded in 2017, towards the end of 2017. I was working for one of Canada’s larger GC companies at the time, and the boss came to me and said, “Okay. We need you to source all of the opportunities for our business unit across Canada.” And I’m like, “Do you understand what that means?” And it was a, “Nope, don’t care. You have to go do this now.” So went home and started to look at the problem, because public procurement is so severely fractured across North America. It’s really, really fractured.

Every municipality will have their own tender hosting thing. And when you’re looking at bidding on work, like schools, libraries, water infrastructure, this is where you have to go to find these opportunities, and they can be all over the place. And so, started to look at this and realized, “Okay. This is something that we can start to automate. Let’s build a collection system that will go out and grab all of these opportunities.” So built that, released it out into the wild, just on my own stuff. There was no business plan for it, and it went nuts and grabbed, in one night, thousands of opportunities.

And I started to look at this and I’m like, “Wow, this is an abject train wreck,” because one of the opportunities that came across was a public procurement opportunity for breast implants, and I’m like, “What is this?” And so, of course, I go and look at this. It was for the Vancouver Cancer Institute, and I’m like, “Okay. This actually makes sense.” But then I’m like, “Wow, do we have a massive problem here.” Because that same buyer who’s working for the Vancouver Cancer Institute is buying these medical pieces on Monday. On Tuesday, they’re asked by the facilities crew to put out a project to retrofit all the lighting in the facility for LED lighting. And then on Wednesday, facilities comes to them and says, “We also need new heat pumps.” And then on Thursday, the doctors come to them again and say, “Hey, we need all new medical gowns.”

So you’ve got this procurement team, and they might be three or four people, but there’s no way that they have the spectrum of knowledge in detail to start to procure what they’re being asked for, and this is just one microcosm of an organization. So a lot of these opportunities can be misidentified on the NAICS codes. They can be posted in the wrong areas. So if you’re the construction company that’s looking for those projects, it’s finding a needle in a massive haystack. But that’s when I started to look at it and said, “Okay. Machine learning was just starting to take off then. Natural language processing was starting to become a thing.” And I’m like, “This is the perfect application of that technology.”

So I went and built the first AI just, again, to target the stuff that I was asked for in my job. And then one evening, I was playing video games online with my buddy from back in Ottawa there, and we were just chatting about stuff, and I’m like, “Yeah, this is the thing that I’m tinkering with.” And I showed it to him, and he’s like, “Oh, that’s kind of cool.” And then I went away, and then a couple weeks later, he calls me up, he’s like, “Hey man, I went and did some research. I can’t find anybody that’s doing what you’re doing.” And he’s like, “I can’t find anything that does what your platform’s doing for you right now. Do you want to start a company?” And so, I’m like, “Sure, let’s do that.”

So we started in 2017, and it basically ran. We put out a platform to handle it. It was our first platform. We call it Tenders. And basically, it aggregates, sorts, and reduces the time that companies spend searching for opportunities from roughly nine to 18 hours a week, depending on how many people you have doing it and what they’re doing, down to about 20 minutes. And we’ve had some people benchmark it. One of the GCs on the platform benchmarked it against their BD group. So they had a team of five people in BD. Three. Three people in BD, if I recall correctly.

And the platform found five opportunities that the BD team had missed and only missed one that the BD team found. And so, it’s a fascinating automation there. But out of that, we started the company and basically ran it off the side of the desk. I was just sitting there, I’m like, “I still had my day job, still working in construction,” right up until last year, actually. And last year, January, the company had started. We had released our estimating platform to drill down into the next level of the front end of construction, and I realized, “Wow, this is working. 100-hour weeks is getting to be a bit crazy.”

And so, I left construction at that point to focus full-time on the contact side of things. So that is basically how PataBid got started. The name PataBid is a throwback to being born in Kenya. Pata is Swahili for search, find, or get married to, and I’m like, “That pretty much applies to everything at the front end of construction. You are always married to those projects and you really hope it’s a good marriage.” Yeah. So that’s basically PataBid.

Steven Rossi:

Nice. Yeah. That’s great. That’s really interesting. I like the name story too and how you got started. That was really cool. So can you explain to everyone how PataBid benefits that? So for prospective users or your current users, what benefits they’re seeing?

Melvin Newman:

So the end goal is always to do more with less. The construction industry, due to various societal forces over the last decade, has not had the influx of personnel. So a large percentage of my personal generation went into technology, went into numerous other industries, and construction was in no way a focus. Personal belief. That was shortsighted. But now, the reality is, construction is forced to do a lot more with a lot less, and time is the number one commodity that construction companies need to recoup.

So we bring aggressive automation using machine learning, using scraping technologies on the tender side of things, using our machine learning AIs built into our estimating platforms. And that’s what we bring into this to aggressively recoup time. So when you’re that owner-operator just starting out, you’re that master electrician that, “Hey, you’ve graduated to the next level. You started your company,” we’re there so that when you’re bidding those jobs at 11:00 at night, we can try to shorten that time up as much as possible so that you can get sleep and have a family life, and also do it more accurately.

So because of the use of AI, the natural language processing, the image segmentation side of things, we’re also able to start to help these people protect themselves. So, again, when you’re starting out that business, you have no idea what liquidated damages are. You have no idea what these contractual terms are. Well, that’s what we’re starting to build into the products, is that ability to run a first pass. We’re never going to replace your knowledge as a tradesman. We can’t. And this is one of the fundamental weaknesses of ChatGPT, as an example. The same thing applies to the AIs that we’re building.

ChatGPT, for example, has been trained on everything. So the technology that they use to do that is actually fascinating, the distributed massive model that they use trained on 10,000 GPUs that they had. That part of it was fantastic, but the problem with training on everything is that it overnormalizes. So an AI, at its core, normalizes everything that it comes into. We, as humans, actually do the same thing. That’s why we have biases.

And everybody takes the word bias as a negative connotation, and in many ways, it actually is. But when you’re in construction and you’re working in Ottawa, you’re working in Toronto, you actually have to be biased to that region. So if we train an AI on all of construction, the problem is, it’s not going to necessarily be specific to your region.

So what it’s there to do is accelerate what you do, but it may not know all the local conditions that you still have to put in, but it’s going to give you back that first 75, 80% of the effort that you’re going to take on a project. It’s going to help you offload that, and then it becomes the higher-level work that you’re going to do. So that is what PataBid is all about, is to bring time back to our clients and recoup that for them.

Steven Rossi:

Nice. Yeah. That’s great. I think that’s a great approach that you’re not looking to replace anything. You’re looking to sort of complement things.

Melvin Newman:

Philosophically, I mean, if you want to head down that black hole, I don’t think it’s possible for AI to do that, but I think that it’s going to be the tool that helps us in a lot of those menial tasks.

Steven Rossi:

Yeah, for sure. That’s great. So I know that you guys are focusing recently a lot on your estimating part of the company. Can you tell us, compared to, you touched on the traditional pen-and-paper process, how PataBid estimating differs from that? And also, do you find that you receive a lot of pushback or hesitation to adopt the software because it’s so different?

Melvin Newman:

It’s fascinating. That’s an excellent question. So yes, it’s a multifaceted question. So PataBid estimating is, we want to, again, unify everything to mitigate risk, bring back that time. So in our estimating platform, we’ve actually fully integrated the Tenders platform into it. So users who use the estimating product just as a side effect can start to find more work to bid on. And so, we’re trying to unify all of those pieces of the front end.

The estimating software itself is fully unified from drawings to spec, to closeout price. So you have a central knowledge base for your company. Pen and paper is literally the modern-day purgatory. That’s all I can say about it. When I started as an estimator, I started out in project management and then moved into estimating because, I’ll be perfectly transparent, I’m probably one of the most weirdest people in the world. I love estimating. I get a kick out of it. The chaos of day of closing and all the strategies to build up for it and to go and win that project is, it’s just so exciting, and there’s so much in there to touch on.

But started with pen and paper, and I looked at this and I’m like, “There’s just no time for this anymore.” Literally, the function of printing out drawings takes time now, and you can miss stuff. And then the best part was, we had closets full of racks of drawings. And I’m looking at this and I’m like, “Nobody remembers at all what happened in there, and there’s no way to search for that history.” So I started to look at this. I’m like, “We’ve got to digitize this,” because at the core, at end of the day, digital takeoff, yes, it can accelerate things, because when you’re working on pen and paper, you mark up that drawing, you put it on a tick sheet, you take that tick sheet, you put it into another sheet, you take that other sheet, you add labor, material costs to it from your various sources, then you break out a calculator.

And I love this. When we were closing jobs, we would get three estimators together. It would usually be myself, one of the estimators, and the division manager. And we would all sit down at the table with our calculators and we would run through all the sheets and calculate it up, and we were not allowed to close the job until at least two of the calculators came out with the same number, and I’m like, “You’re still only 66% confident on this multimillion-dollar project.”

And then you’d find out months later, somebody had moved a line somewhere and the calculations just didn’t work. So the next step was to move into Excel. Excel is fantastic in that it’s so incredibly powerful. The problem is, it’s so incredibly powerful. And if you don’t put rules, very strict rules around it, people will blow it up and it will end very badly on projects. I’ve seen that happen.

So that’s where we built this estimating package to unify and tie everything in your estimate back to the source material, because at the end of the day, the source material is what you’re building. So why mark up the drawing which you’re going to lose? Because it usually takes six to eight weeks to find out you’ve won a project, and the time is shorter if you’re in, say, residential. It’s also longer if you’re in big, major commercial projects, but the average is anywhere from six to eight weeks to get that contract.

And then you get that contract out of the blue, the GC calls you up and says, “Hey, congratulations. I carried you. Let’s negotiate, sign a contract, and get going. By the way, I’ve already mobilized on-site, so I need you there tomorrow.” And you’re left sitting there like, “Where did I put those drawings? What did I do with all of this? I’ve bid 10 jobs in the meantime. I don’t even remember this.” And so, when you’re doing that process, it becomes hellish and very, very error-prone.

So in PataBid, the number one thing that we focus on is tying back to that source material. So if you put something on a drawing, if you draft something, like we have a whole drafting module built right in, it’s not there to take on AutoCAD. It’s there to make your napkin sketches look really professional. But when you put something on that drawing, whether it’s a wall or a plug, it doesn’t matter what it is, the moment you put it on, it goes into your estimate and it’s tied right back. If you click on that in the estimate, it’s going to show up on the drawing, what you’ve clicked on, if you do it the other way around.

So you can have confidence that if it’s shown and highlighted, it’s there. It’s in your price. If it’s not shown, there’s no more argument. You can go back to the owner, and the famous one is on the residentials. All they get is a layout. All they get is a site layout, an architectural drawing, or in design-build. Well, now they can actually put those drawings together, send that back to the client, and say, “Here’s what you get,” so that a year later, when you’re putting up those condo facilities and the owner comes in and says, “Actually, I want six pot lights here,” you can say, “The drawing that I gave you showed four. I’m happy to do six, but here’s your change order,” and there’s no more argument.

So that’s kind of the key risk mitigator, the ability to tie right back to the source material. And you’re only doing things once. There’s no tick sheets that you then have to go enter. There’s none of that. You highlight it, it’s in the estimate, you close it, you have a price. That’s the end goal.

Steven Rossi:

Yeah. That’s great. I could see how beneficial and time-saving that must be for everyone involved.

Melvin Newman:

Oh, huge. And that’s not even AI. That’s just literally automation at that point. And then you start to layer the AI on top of that, and you have something where, again, you’re taking stuff from 20 hours down to an hour.

Steven Rossi:

For sure. Yeah. Let’s dive in a bit more. You mentioned the AI takes everything so much further. Can you tell us how you’re incorporating AI into the system now and what it’s doing to help your users?

Melvin Newman:

Yes. So machine learning. I like to call it that, because AI is more synonymous with automation. But the reality of what the next level is is the machine learning aspect, the ability for these AIs to learn from the clients. So we’ve got those marked-up drawings now. So we can actually train the AIs on that aspect of it and to get the diversity. So the problem with construction drawings, for example, they are incredibly informationally dense, but contextually weak.

So when you’re teaching an AI, like we’ve got… I’m not sure if you’re familiar with the Mask R-CNN AIs or the YOLO AIs that are used out there right now. I mean, everybody has heard of deepfakes. That’s a little bit of a different type of AI. But they’re used to seeing, like being able to pull people out of an image. Right? So you take a picture outside and you tell this AI, or you take a video feed, “Pick all the people out for me.” That’s actually easier for these AIs to do because they have so much context. They know what isn’t a human.

When you look at a construction drawing, it’s black and white lines. There’s no background. The background is white. So it’s a far more challenging situation to train AIs on how to do this, and it’s a very different approach that we took to training our AI, and our AI is a very deep learning. I’m nerding out. I apologize here. But it’s able to start to pull out that context and generate it, and each drawing type in construction is wildly different. So you’ve got, in pipe fabrication, isometric drawings, and those have a three-dimensional view on a two-dimensional drawing of a chunk of pipe with a bill of materials that looks totally different from a civil topographical drawing for the civil earthmoving guys to go in and prep for a new neighborhood.

So those guys have to go in and move massive amounts of dirt. So those drawing sets look totally different, and yet the AI has to know what that is so that it can go after what it’s targeting. So that’s been a fascinating experience to build into our AI, and we’ve done it. We’re still continuously training it. And what’s really nice though is, once you have these structures in place, the rest of it becomes more of a training situation.

We like to call our AI polymorphic, so it adapts itself to the data that it sees. So we’re able to train it on a lot of these different things. And then once you’ve got these identified, this is something that I haven’t had time yet to get into, but I really want to get into those civil topographical things. So when you’re looking at civil work, all that matters is that your trucks run the most efficient route in the least amount of time, because everything is basically a fuel and maintenance charge when you’re moving large amounts of dirt.

And I’ve talked to some guys about this, and they’re like, “Yeah, the real challenge is figuring out how to do this.” And I looked at it one day, and I’m like, “This topographical map looks exactly like a CNC path for a CNC machine.” All the algorithms have been around for decades for plotting the most efficient tool paths in a CNC machine. We can literally take that and say, “Okay. Here’s my 3D model. Yes, instead of being a part that’s six by six inches, now it’s a kilometer by a kilometer, but it’s the exact same function.” And the earth-scraper becomes your machine tool, and it could literally output G-code to drive that machine for you over the land. That’s where we’re headed.

And again, AI actually doesn’t take as much of a front seat in that situation. That’s more automation, but where the AI comes in is when you throw a set of drawings at this and the machine now understands what it’s looking at. It’s like, “Okay. This is a topographical map for my new biodiesel facility, and this is now the piping schematics for it, and this is the electrical schematics,” and then understanding what to do in those situations. And all of that is only 50% of what happens in construction, because what happens next when you start to generate that information? That is the more exciting start, like future.

You take deepfakes and you say, “Hey, start to route for me this sort of… Start to route pipe. Start to route wire, and route it intelligently at the time of tender,” for example. So right at the very front end of the business, when you have none of this information, you can start to have it automatically start to generate this. And it’s not going to be perfect. It never is, but it gets you going. So yeah, what we’re about is bringing that AI in and we’re really focused on that first 50% right now so that we can get that nailed down and then move on into the next steps.

Figuring out the algorithm to start to tie that together was the secret sauce, is the secret sauce. And then AIs are fascinating. They’re very similar to humans in the way they learn. The problem with them is they actually have no life experience. So you try to teach an AI what a wall is. You try to teach an AI what a piece of pipe is. It’s never seen that. It has no idea what that is. So, I mean, our AIs start with a common dataset. It’s the COCO dataset, where we give it some of that life experience. I think it’s pretty much that was the gist of where PataBid’s at with our AI development, what we see as the future in here, and it’s a fantastic future.

Steven Rossi:

Yes.

Melvin Newman:

It’s really fascinating to see where we’re going to be able to help construction professionals, really, at the end of the day is where it’s at.

Steven Rossi:

So next, can you share some of the success stories in different projects that you’ve seen? If there’s a specific one that stands out to you, or maybe there’s a few?

Melvin Newman:

Yeah. No. It’s been fascinating. Since we released the estimating platform last year… Well, I mean, early on, one of my favorite success stories on the Tenders side was, we had a client that was one of the, again, national general contractors here in Canada, and I pitched the Tenders platform to them, and they were very hesitant. They weren’t necessarily technologically go-getting on that kind of stuff. And so, I went back and forth with the manager, and finally, he was like, “Okay. Let’s give this a try and see what happens.” He’s like, “We’ve got three people right now that source our opportunities. So we’ll do a trial run with your Tenders platform and see how it can go.”

And so, we did a trial run. He’s like, “Okay. Yeah. We’ll buy a license for this, and then once our champion of this…” One of the people got right on to it right away, and the manager’s like, “Yup. Once she gives us the go-ahead in a couple weeks, we’ll buy the remaining licenses.” And I’m like, “Okay. Cool.” So I waited two, three weeks and I called him back, and I’m like, “Hey, you still want to get those licenses?” He’s like, “Yeah.” He’s like, “We’re going to stick with the one we have because we don’t need the other people doing this now. It’s so easy now, this one person can manage it for our entire division, and even for her now, it takes her less than a morning to do it.” I’m like, “That’s awesome.” But at the same time, I’m like, “Aw.” I wanted those two other sales, but I’m like, “Man.”

And so, then that company’s actual other divisions across Canada got in on it and are still using it. But basically, they took it from having three people doing this one function down to one person able to do that function in half the time, and those other people got to move on to the estimating side of things. And I was chatting with them after this happened. They’re like, “Yeah, that’s such a terrible thing to try to go and find these opportunities. It’s the most boring, repetitive.” So when we talk to companies, we’re like, “No, you’re not going to get rid of your staff. You’re going to give their lives meaning, because this is a terrible thing to not automate.”

And then on the estimating side, one of my favorite ones was one of our clients on the West Coast. Residential guy, so not some big, multimillion-dollar corporation. He was just getting going, and he was one of our early adopters on the estimating platform, and he calls me up late Friday night one time and he’s like, “Look, I’m working on this project. Client wants the price right away. Can you just make sure that it’s going in right?” And I’m like, “Yeah. Sure. We’ll take a look at it.”

So ran over it and I looked at him, I’m like, “Dude, export the drawing and send it with your quote.” And he was like, “Why would I do that?” I’m like, “Because you’ve done a whole layout here just in the function of estimating.” I’m like, “You’ve shown all the lights.” I’m like, “It’s going to protect you. It’s going to mitigate your risk on the project, and more importantly, you’re going to be the only electrician that does this, and it takes you exactly 30 seconds longer to export this and send it with your quote.” He was like, “Okay.” So he did that.

He calls me Saturday morning, and he’s like, “I just got off the phone with the client. Absolutely blown away by what I submitted to him. I have the job. I start Monday.” I’m like, “There you go. That is what we’re here to do.” And then he called me up a few weeks later, and he’s like, “Do you have any idea, man?” He’s like, “You have taken my estimating from one of these houses would take me 20 hours to lay out on paper, including all the printing of it and all this stuff, and then I couldn’t send it to the client.” So he’s like, “I had to mitigate my risks through describing everything in the quotes.” He’s like, “You’ve taken it down. I can do this house now in two hours before going to bed and I can submit it to the client and the client is floored by it.”

And we’ve started to hear that over and over again from our clients. And then we have some other features in there that let you… If you’re doing massive high-rises with repetitive things in there, you can actually go and build… We call them typicals. So if you’re doing a hotel, for example, you’re going to have 30 stories and you’re going to have maybe five different types of rooms. And so, what you can do is take off each of those types of rooms and then tell the AI, “Go and count all of these for me.” And then it will go and crawl through drawing by drawing and count those for you and dramatically speed up.

So you can now do an estimate in a matter of a couple of days and get out 10,000 man-hours out of that, depending on the type of project. And then if you get into the more complex projects, you can still do that simply by the fact that you can use the AI to count all of your instrumentation, all of your doors, all of your windows, those kind of things, and very quickly start to put that together. So yeah, that is how the AI is pulling all of this together.

Steven Rossi:

So just one last question before we wrap up. Could you tell me, I think you’ve touched on this a little bit already, but what role you see PataBid playing in the future of the construction industry and how you see the software evolving as the industry changes?

Melvin Newman:

Yeah. So I see PataBid getting into more of the generative side of things. So as projects move more towards design-build and the time frames to bid on those projects gets more and more compressed, we’re going to have to start to use AI to generate that kind of information and put together much more quickly the cost estimates, if you will, and then being able to tie that into the site. Okay. Now you have this. How do you transmit that information to the staff on-site? How do you unify remote sites locally? If you’re a larger organization, how do you bring your subject matter experts from all over your different divisions to be able to work on one thing from anywhere?

So we see a lot of that, the connectivity side of things, along with the generative side of the information, and really unifying that estimating process from start to finish. Our focus is 100% on the front end of business. We want to conquer that aspect of business and bring that together, because it’s a severely under-serviced market out there. And that’s where companies get into trouble, because if you don’t understand what you’re committing to right at the beginning, it doesn’t matter how excellent your project management processes are, how excellent your execution might be. If that estimate is screwed up, you’ve got a problem.

And so, that’s really where we see the future of PataBid, is to allow you in those very small windows. You might have three to four weeks to bid a job that’s going to take you two to three years to build. In my mind, that’s crazy. And a lot of companies miss that because they’re like, “Yeah, the estimate only takes three weeks.” I’m like, “Yes, but every safety incident, every financial risk, every contractual risk is actually committed to when you submit that price.”

And it doesn’t matter if that price was generated in three weeks. That’s horrifying that you would do that, but that’s where the industry is at. But in that two- to three-year build time or however long that project is, I mean, the Boston Big Dig was 100 years. That’s a crazy project. But every one of those financial risks, every one of those things is committed to at the estimate stage. So we have to get that right as an industry.

Steven Rossi:

Absolutely. Yeah. That’s a great point.

Melvin Newman:

Yup. Very good. That’s where PataBid is.

Steven Rossi:

Nice. So just lastly, before we wrap up, if our listeners are looking to learn more about PataBid and to get started with you guys, where should they go and what should they do?

Melvin Newman:

Absolutely. So we’ve got our website, https://patabid.com. So that’s a good first entry point. We also do have our YouTube channel, where we’ve uploaded tutorial videos and you can get an in-depth view into what the software can do for you, how it functions across all of our platforms. And then at any time, you can feel free to reach out to myself, melvin@patabid.com, and connect that way or via LinkedIn. So, I mean, we have a number of ways of getting in touch with us and we want to hear from our clients.

Steven Rossi:

That’s great. Thank you so much.

Melvin Newman:

Thank you. This has been a pleasure. I hope it hasn’t been too much down the rabbit hole of nerdery there.

Steven Rossi:

No. Not at all.

Melvin Newman:

Yup. Estimating nerd at large here.

Steven Rossi:

It’s great to see someone so passionate and also, I found, personally being interested in technology, and it was very interesting hearing you to go a bit deeper into some of those things as well.

Melvin Newman:

Absolutely. The future is going to be awesome.

Steven Rossi:

Yeah.

Melvin Newman:

Yeah. And the future is starting to happen today, so it’s an exciting time to be in construction. To all the listeners out there who might not be in construction or have kids, construction’s a good place to get to.

Steven Rossi:

For sure.

Melvin Newman:

Very good. Well, thank you so much.

Steven Rossi:

Very good. Thanks.