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gecko robotics builds wall climbing robots and enterprise software to maintain and protect essential
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infrastructure he is the CEO and co-founder at Gecko robotics Jake thanks for joining me today every hour you save
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you're saving potentially millions of dollars Hardware is hard be very careful there's a lot of really important
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problem to solve there's so much sex appeal to building new things you got to get the business model right and the
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business model has to make a CEO or CFO give a there is a huge fire going on right now
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at Philadelphia Energy Solutions oh my gosh again look at this guys look at this video right now today the Navy
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remains a formidable fighting force but even officers within the service have questioned its Readiness at a missile
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silo we visited time and frigid weather had clearly taken their toll developing right now gushing for hours with no end
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in sight thousands of barrels of crude oil spilling from a uh the report does an estimate of what
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the need is to bring the overall grade up to a b which is what the society sort of determines to be adequate and it's
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like $4.59 trillion [Music] [Music] [Music] [Music] yeah all right hi I'm Jake the founder and CEO of
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gecko robotics a company that makes robots and software to help diagnose the health of the built world now it started
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in a college dorm my college dorm is now a company that manages over 500,000 of the world's most important and critical
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pieces of infrastructure now the structures that we use to power civilization have reached their useful
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life it's a huge problem and it's getting way worse but it's a problem that you probably don't think about very
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much but you should in New York for example there are over 177,000 Bridges most of which are in New York City and
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guess how many of those bridges are not in need of immediate repairs only six see maintaining things has always
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been an afterthought but that afterthought is now a 4.59 trillion domestic problem and by the way it's getting
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worse it's holding us back for example the military spends 40% of their budget over $400 billion on
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maintenance not on building new things just keeping old things working and Fortune 500 companies will lose $1 1.5
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trillion every single year because of catastrophic failures that were unpredictable
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and our best defense to stop that from happening hasn't changed in over 60 years it's this this is Joe and Joe's on
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a rope now Joe's armed with a handheld sensor and what looks like an excruciating
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wedgie now Joe is our best chance to ensure that pipelines don't explode that Bridges don't collapse that dams don't
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fail and that airplanes don't disassemble mid-flight it's an impossible job unfortunately for
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Joe you see we obsess about how software has changed everything for everyone it's
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eating the world right it's important to remember that for the guys behind me it's actually never help them you see
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the data that we need to prevent catastrophes from happening in the built World simply doesn't
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exist and without data what can software do now I became obsessed with this problem in college I was studying
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electrical engineering and my obsession for energy took me to a local power plant in Pennsylvania I wanted to se
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power was made and so I decided to dive in head first now I I actually dove in head first straight to this hole and
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when you got through this hole you got into a 200 foot tall steel tubed box the length and the width of a football field
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this is a power plant boiler and the boiler's job was to turn water into steam by getting really hot see the
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problem is as the plant manager Jeff told me that 40% of the time this boiler would be shut down because of pressure
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tube explosions it would cost them $2 million every single day they were down this is
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a small little power plant and so I asked Jeff how do you stop this from happening and he says well we send up
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humans on ropes looking for invisible defects then he began to tear up and he told me a story about how his best
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friend fell and died the year before doing one of these inspections and he fell and died in the exact spot I was
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standing so I was floored by the story and so I had to do something about it so I went back to my college storm
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and started building the First wall cling robot now I armed this robot with ultrasonic sensors just like doctors use
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for sonograms and I deployed that robot into the boiler saving the plant manager
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Jeff $30 million just that year and I became absolutely obsessed with how we understand the health of the
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built structures that we use every single day and so I started a company and I boot shaed that company
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for three years pouring my life savings into it I slept on my best friend's apartment floor and I was down to the
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last $100 two things happened within two weeks first I got an offer to buy the company from a company that makes power
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plants and then second two partners from a group called y combinator said that if
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I stay poor and kept on building the vision that one day gecko would change everything that we knew about built
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structures so I decided to stay poor and keep building the vision so we launched
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the company in 2016 and we began to deploy the technology into the oil and gas manufacturing public infrastructure and
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even defense sectors we had to build robots that could climb and Traverse and get sensors into all different kinds of
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surfaces geometries conditions and once you have 500,000 assets you have to climb around you begin to iterate your
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robots really really well to be able to handle these kinds of environments and it became clear that contrary to popular
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belief from the VCS at the time the robots were the mo because they could get sensors to places that could never
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be gotten to before we can convert atoms into bits and so I wanted to double down
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on that moat and so we started building robots that could fly swim crawl and walk up any surface we begin to build
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autonomous platform to arm those robots to be a to go to places so that humans didn't have to be
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in dangerous environments we built and became the best in the world of building ultrasonic sensors electromagnetic
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sensors as well as lasers to be able to see and understand what was going on inside of Steels composits and concrete
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we built fixed sensors that could stream live information and data sets to us both the health but also the operational
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conditions of those assets itself and we built an API platform for robots called
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so that other robotic companies could actually be used on our platform and streaming data and information live to
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our customers and after 10 years of collecting data on almost every structure imaginable we launched
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Canal our Ai and Robotics powered operating platform to put those data layers to use for our customers you see
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when you start building software by first starting out with the data layers and then building up you're severely
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advantaged because you can build software from principles and our ontology now was able to affect folks
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from the ground level the guys on the ropes all the way through to the Executive Suite it was extremely
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powerful but post is talking about it let's actually dive into an example so to do that I'm going to take you to
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Georgia to a manufacturing facility that me and you me and you use in the bathroom every single
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day now this facility has thousands of assets and billions of dollars worth of infrastructure and so they wanted us to
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prove out over 50 assets what we could actually do so I'm going to take you through one of those assets today a
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sulfuric acid tank so first what we do is we gather information about the asset by customers
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sending us their metadata and we build out a digital representation of that asset inside of
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Canever and then we send in our robots first we use a drone you can see over here now the Drone is armed with with
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cameras that are doing a photog gometric scan of the asset it enriches the asset
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model itself being able to identify different kinds of defects using Point clouds so corrosion areas like over here
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we're able to categorize and locate and then dents and cracks as well enriching the data asset model we want to go
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further than that we incorporate other sorts of components like piping and pumps that you see here both in the
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inlet and Outlet this is extremely important and valuable because we keep on adding data layers and the next one
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is a dog come here boy good dog hey everyone say hi please yeah there we go nice so let me let me pet him real
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quick he likes to be pet yeah good boy so this dog will walk around to dangerous environments gathering
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information about what's going on on the infrastructure now what's important also
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to understand is that because of an API platform for robots we've built an extensible way for a company like
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anybotics one of our partners to be able to gather information in data sets and this robot is extremely exciting because
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it's built to be explosion proof meaning it can go inside of oil and gas facilities nuclear facilities and Beyond
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it's gathering information like you see above thermal imaging to understand what's going on with the asset all this
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data is really important when we do optimizations later now we want to begin to continue to gather more information
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about the asset so we send in submersible robots these submersible robots are looking at the deformation
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because of the weight the liquid as well as the health of the assets floor to prevent things like that um oil tanker
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leaking into rivers and once we've gotten this and the customer is really excited because we can do this W they're
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online we then send in our robots and we rise collecting information and data while the C while the customer's tanks
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are still in operation now these robots that you see right here are armed with ultrasonic sensors cameras and the IMU
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on board to ensure that we can do this autonomously Gathering terabytes of data in 12 hours for this tank a process that
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used to take about a month to do while the asset was shut down costing millions of dollars and we can do this in a way
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as well that ensures we can localize data points to begin to run optimizations and in this case because
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these assets are supposed to be reaching their useful life or reached it we can extend the useful life of the
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infrastructure and so for this example we can tell them what to fix in five and 10 years to extend the useful life so
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that this asset continues to be able to uh do its function opposed to having to replace it for $8 million which was what
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the plant thought they would have to do so once we do that predictive model we work with maintenance companies to
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ensure that they actually take action on that and we update the model to ensure that a source of Truth
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remains next we actually the customer actually wants us to begin to do other optimization so we use fix sensors like
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this that'll stream information about not just the health but also the operating condition
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of the facility you see when you're running a let's say a big manufacturing facility your goal is to figure out how
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to make more product without having stuff blow up U because of a new operating condition now that's never
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before been possible because the data you've been able to work with has been from Joe on a rope and so you don't know
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if you change your throughput or make more product if that'll destroy the assets we're able to run
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optimizations now I'm going to show you that here so this customer was able to because we're streaming information and
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data from the pumps and from the asset itself we were able to figure out how to increase the throughput or make more
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product by about 5% more while only having to incur over 90 days an accelerated um an accelerated damage of
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the asset of about two months equivalent to two months and so we proved that we could do that by actually lowering the
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fill Heights in the tank and increasing the acid concentration level you can see
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the optimization being run right behind me now this was significant because of the ability to not just
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extend the useful life but actually produce more while not having the potential risk of a catastrophic failure
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something never before possible for these companies now let's talk about the outcomes for the customer on average
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over the 50 assets we extended the useful Life by 10 years this affects their p&l and their margin right away
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because of ability to extend your depreciation models and then we created $15 million um of value by being able to
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reduce safety risks as well as Environmental as well as being able to reduce the amount of CBS that customers
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needed to spend and the estimated from the customer was a 4% impact to their margin now all of this optimization and
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information coming in doesn't just help the customer it also helps can lever be exceptional in a compounding way at
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running facilities more efficiently and so now you have an ability to have an unfair Advantage from from companies
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that are not utilizing technology like this so not just are robots cool but they're actually solving a business
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problem so this has been flying off the shelf as you can imagine since we launched
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Canever this year the 12th largest oil and gas company in the world for example determined that they have 100,000 tanks
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and that we could provide $122,000 of Roi per tank now initially we signed a $30 million contract it's exciting it's
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going to extend to 100 million but it shows how if you adopt technology in a way like this it's
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unfair now on the defense side we're working with the uh Air Force on $130 billion modernization program now they
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have to modernize over 400 nuclear missile silos and the best way to determine how to modernize or what the
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scope was to improve the missile silos was I kid you not Joe on a rope with a hammer who was listening to the sound
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that the silos made when he hit it so now gecko is helping to improve what the modernization scope actually
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should be and it points out something interesting those that are determining the scope and size of these
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modernization Pro projects are the same ones incentivized for that amount of dollars to be as high as it can
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be now on the Navy side one of the biggest problems is only a third of our ships are available to patrol and deter
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conflict around the world and the reason why is because of Maintenance Cycles so we worked with uh the Navy to
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improve in this case it was Joe on a skateboard on his belly over a flight deck looking at different different
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areas trying to gather information and data set we improve that to be able to reduce
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labor by 85% and improve the turnaround times for Flight deex Alone by about a month so now we're doing tens of
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Millions with a navy on flight decks and we're extending that to ballast tanks hulls as well as commercial Maritime
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it's really exciting and then on the energy manufacturing sector that's where most of our 78 Fe accounts lie with big
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contracts like xon BP and Beyond now one thing that's extremely exciting is that it turns out if
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pipelines explode or when oil leaks into rivers it's pretty bad for the environment so the studies show that by
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2030 in the US you can reduce emissions by about 18% if you can stop those kind of things from happening so technology
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is available today to make a drastic impact on Net Zero and then it turns out as well if
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you're the best in the world of understanding the health of built structures you're actually very
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advantaged in building new things and so that's what the Admiral in charge of $132 billion nuclear um submarine
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project called the Columbia class determined so now we're helping to create the most advanced submarine in
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the world from the beginning to the production end and it gives you a peak into what's
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coming now this is why it matters you see I'm not crazy building robotics Material Science AI software
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sensor company it's really freaking hard um but I had no choice you see the promise of AI from AI compan
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to make impacts in these industries have gone empty for years and years and years
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and it's no wonder why they're building their foundational models off of Joe's data data that looks like
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this this is a real report from one of our customers before they used gecko it's no wonder that AI hasn't made the
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impact in of the promise that it was supposed to so this is why we built geeko and why
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I believe because of software being commoditized that first order data companies will dominate the next 10 and
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20 years in software and my journey through the rust has given me both a pragmatism and
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optimism about the future a future where understanding how things work helps you
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build new things understanding how to use Ai and Robotics in these real practical
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ways a reality where we can understand the health of the built structures all around us just as as well as we
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understand our own health and you begin to see robots of course in normal society but these
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robots won't be built for doing back flips or folding laundry they're going to be built to help realize the impact
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of AI for the built world with systems like Canever thank you thank you that was awesome
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yeah come here puppy oh David Zach showed up everybody doggy hey Z that's a robotic
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dog it's kind you're kind of dog oh go to sax go to sax go give him a kiss oh there we go SX is very
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affectionate so you can pet him if you want David you can pet him s here where where do you pet him exactly there you
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go that was a lot of love yeah I am experiencing oh companionship from this excited yeah it's definitely it's
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definitely a nice dog yeah nice dog doesn't bitey I think one thing that would be
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great based on the kinds of customers you have can you tell us a little bit about the sales life cycle and the type
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of deals you do I mean it's so interesting to is it like an Enterprise software type sale and you know when
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you're going in and doing physical work I mean I didn't know where to sit were you worried about the dog no
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this was it's a very poorly organized conference yeah let's talk about that yeah we we only told you where to sit
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five times in the last four minutes but I don't understand these images I have you know literally we go in there after
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and like Sergey comes he does his first thing and I'm like Ser oh yeah do you have any food I go out to the food and
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it's just like rubber conference chicking in the VIP speaker area and I'm like free birg can we just get some
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sushi from noou we should go through all the details yeah no tell us about the sales life cycle so what are the kinds
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of deals you not talking about rubber chicken right now we've got a panel uh but yeah tell us about the sales life
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cycle the juice has been really good by the way I like thank you um yeah so so the life cycle it's been it's been it's
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been wild so you know gecko actually became profitable in 2017 right after YC's launch in 2016 and so you were a YC
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company yes 2016 and um what was interesting about that was you know we decided to build a
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company very for deployed so instead of building robots and Labs actually funny story one of the VCS you had here last
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year offered a bunch of money at YC um for us not to leave and go back to Pittsburgh and do this forward deployed
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motion of building robots but instead build it in a lab and I turned that down because I just fundamentally didn't
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believe in that way of building and so um but so we decided to launch into the um and build robots like
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I've literally soldered in these environments um before and and just figure out how to make the robots work
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in reality in the real world and so the sales motion was basically we would go to the plant managers sometimes I'd call
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and be like hey my pizza guy like you know where's the where's the plan manager can I talk to him and I'd get
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figure out how to get to the plan managers and then I'd uh convince them to let us work with them in their
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facilities and so started out that way by selling to the folks who need this the most yeah and so but now I'm talking
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to um obviously CTO and and CFOs because our products are actually very Financial
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um it helps with depreciation models it helps with optimizations but we started by just selling to the folks in the
00:22:05
ground and building the robot um by failing a bunch of times there and fixing it live but now we have uh a
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great platform and so now when customers buy gecko the only way they can buy it is through software so they buy a can
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lever and they bought they buy an implementation of the software which is the robots getting the data and then
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they pay for a license um for the software and we try to make data refreshes which is basically robots
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going out and collecting more information free is there a custom is there a custom deployment in every one
00:22:33
of these because they've all got to have different facilities and how hard is it
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to kind of customize or do you have standard standardization now in each deployment they kind of do a Chinese
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menu type selection we try so so it's a great question we we started in the beginning by letting the customers pick
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what kinds of data layers they want they want so data layers basically mean what
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kind of robots now we actually don't allow them to do that we follow all the standards whatever like API which is
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like these governing bodies about how to take care of your infrastructure um but
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then we go way beyond that because I want to create an incredible user experience that they cannot revert back
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from Jak there's um there's all kinds of crippling infrastructure problems around
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the world that are not necessarily tied to some of the obvious Industries like oil and gas so I'll give you two
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examples one was what happened in Baltimore where you know this who knows how it happened but basically the bridge
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just collapsed in a situation that and maybe it was supposed to be and and it did another example was a few years ago
00:23:31
in genua in Italy an entire slab of a bridge just collapsed and it fell on top of uh um an environment and killed a
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bunch of innocent civilians so there's I think a public safety requirement here which is like some of
00:23:46
this stuff was either designed poorly or designed very quickly how much of that is observable by these kinds of robots
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and how do you convince folks that Beyond depreciation and Financial motivations there's a you know a real
00:24:00
need to make sure that this public infrastructure is safe and you guys can secure it um great question so the
00:24:07
answer to of how can we actually get information on those types of incidents is yes um we we like you can look at a
00:24:13
concrete bridge and say hey there's some Decay here or there's something that's happening in the giring here and you can
00:24:19
recognize that and learn and be able to say wait a minute you need to send inspectors or shut the bridge down or
00:24:27
stop and figure this out you first want to do so what the robots are really good
00:24:30
at is getting a crap ton of data about the assets and then you can pinpoint exactly where to put fixed sensors in
00:24:36
specific locations that would be indicative but then also because of our of of our you know we have this like
00:24:42
really interesting data set that tells us because of so many different types of U situations um what kinds of potential
00:24:50
issues are occurring that we can extrapolate out to these types of situations that we might be not as
00:24:55
familiar with so we'll put fixed sensors on to give us indication and give us an ability to help
00:25:00
prioritize spending and so um you know we just actually signed a a contract with Governor Shiro to do this for
00:25:07
bridges in elany county in Pennsylvania where Pittsburgh is and um we're helping
00:25:12
to modernize um Bridge maintenance and prioritization of budget because what you can see here is you don't
00:25:18
necessarily need to rebuild stuff and in some ways that's not even practical but
00:25:21
you can figure out where to deploy Capital um and then by way did you see this video on X where somebody was going
00:25:27
through the Lincoln Tunnel and it looked like it was about to burst there was like water creaking in it was really
00:25:34
disconcerting yeah but I think it was more of a design feature to actually like alleviate when times when the water
00:25:40
levels were super high but my point is there's all of the stuff that we interact with that it would be good to
00:25:45
know that there's a you know a service out there looking for it and is is there a world where you could also then
00:25:51
theoretically ingest like the actual architectural orad of these things and then also be able to do diffs and VAR
00:25:58
and be able to tell people hey hold on a second this is not conforming to how we
00:26:02
thought it should be behaving yes we do we do pull those in as much as we can but it's important to remember that most
00:26:08
of the infrastructure that I'm talking about is like 60 years old um now on the new build side like for the new Columbia
00:26:15
class submarines for example um there's an issue where like there's not a digital thread you have like 5,000
00:26:20
different contractors that are trying to make us most powerful sub in the world and they're handing paper to each other
00:26:25
um as they build the submarine and so causes one a big a bunch of delays and issues which we're seeing with a lot of
00:26:31
our ability like China for example can outbuild Us by 232 times uh submarines that is or or new chips and it's a a big
00:26:39
part of like our our like we have to be able to figure out how to be smarter when we manufacture and so one of the
00:26:44
ways you can do that is digital threads all the way through the manufacturing process so that we're not like delayed
00:26:50
by handing paper to each other that may or may not be incorrect and for the customers that we work with you know
00:26:56
most of them you know you're looking at drawing that are 60 years old they have never been converted um I we even try to
00:27:02
get asset lists from customers and they like we don't have it so we have to go out and actually build that for them how
00:27:08
should we build a submarine just off topic how should we build it yeah so we don't have 5,000 contractors at well 1%
00:27:15
or 2% the speed of China it's a good it's a good question I think we should Orient our most efficient um way of
00:27:20
building as many components in one place as we can but you have to remember as well you know Congressional members have
00:27:25
their own constituents to advocate for and so they want to bring jobs to their to the local communities and so in a in
00:27:31
a democracy it's really tough actually MH Jake how do you see um where your Bots your robots and let's
00:27:40
say the more traditional generalized humanoid robots intersect when when they meet how do you think about that problem
00:27:45
oh it's a great question um I am so excited to buy as many Optimus robots as possible yeah you're a customer you'll
00:27:52
be a customer 100% you're not going to be a competitor no no no I mean um look at anybotics right here so this is a
00:27:58
this is a swed it's a company based in Switzerland that have an incredible robot and their data doesn't know where
00:28:05
to go and so the idea of robots this is what I firmly believe is that taking them home today is that um you know they
00:28:12
get sensors to places that are really hard to get sensors to and so that information has to be funneled um
00:28:18
somewhere to drive some large business outcome so I really don't think like you know I I'm not of the belief I guess
00:28:25
that when Elon talks about you know two times the amount of um robots as humans that you'll see them in society actually
00:28:32
as much as you maybe you'd think I think they're actually going to be found mostly in these like really dangerous
00:28:37
behind the scenes industrial settings which I in my opinion that's like where they should start for sure because
00:28:43
you'll have to you one you have to those are really complex tasks but two they're
00:28:47
like very beneficial for Humanity um so like is there is there a generalized platform that you've built that allows
00:28:53
you to solve for these different use cases or do you find that there's a lot of application specific engineering
00:28:58
that's required good question so we we we built an API platform for robots where um companies can try their systems
00:29:07
out and we can because we have a go a market we can now test if that robot is producing something valuable from a data
00:29:12
side right and I'm am not actually as interested in robots I can weld or robots I can clean right now mostly I'm
00:29:19
just interested in just like what kind of information and data can we build better operating platforms and systems
00:29:23
on and um so that's that's where I'm starting and we'll begin to add more robots that can do different kinds of
00:29:29
jobs but um you know I think it's you have I think this is where first ordered data sets and and and software companies
00:29:36
are become more and more you know powerful this is why maybe you know um my opinion on on like the the Standalone
00:29:43
SAS model is like I think it's going away um because the companies that are so advantaged with first order data you
00:29:49
can you know just build your own software have a capital markets last question have Capital markets kind of
00:29:55
embraced the story or things you can invest okay yeah um yeah they they really are I think um because
00:30:04
there's a lot of this like hesitation around deep Tech and Hardware historically but you've obviously got an
00:30:08
incredible software layer and great recurring business so you seem to be pretty differentiated in terms of a lot
00:30:13
of the Long Haul build cycles that I think we see out there and it's yeah in Hardware in our case it's very sticky
00:30:22
yeah because you know once you convert from you know paper and you're now not using binders you're using can
00:30:28
yeah um it's it's really hard to go back yeah I just yeah I think it's we've talked before and I think what you're
00:30:34
doing is so inspiring because it feels to me like this technology you know that we've seen over the last 20 years in
00:30:41
iPhones in EVS in sensors um is now allowing us to move from being reactive and trying to figure out what happened
00:30:49
to then saying hey let's be proactive what are the opportunities here to extend life to say you know extend the
00:30:55
life of these assets um and avoid tragedies and I just you know I think the work you're doing is a real
00:31:03
Grinder's work but it's going to save lives and it's going to really save taxpayers money that could be deployed
00:31:08
in other places for beautiful things and so I just want to commend you on doing something that is so essential um in
00:31:15
many times I meet a founder and they are doing something and I just think God I I
00:31:21
don't know if this is going to work or not but I know that this founder is going to figure out a way to make it
00:31:26
work and I I think it's just really rare that somebody cares so much about something and then executes as hard as
00:31:32
you have um and I just want to tell you I personally very much appreciated it because you know when a bridge collapses
00:31:39
I know the one in Italy it's it was a very big tragedy I think it killed 50 odd people and it was privately owned
00:31:44
yeah and there's a you know very very wealthy family that owned it and ultimately sadly no repercussions yeah
00:31:52
same with dams in Brazil same with dams in Brazil right so you know as public infrastructure becomes private
00:31:57
infrastructure then the profit motive supersedes a safety motive you're going to get all these things unless there's
00:32:02
um um some sort of check and balance so long way of saying we very much appreciate this hard work that you've
00:32:07
dedicated last question yeah you're you're you know you you've been in the YC Community for a long time just really
00:32:13
you don't have to say yes or no but have you ever been forced to do any founder mode did you feel pressure have you just
00:32:21
just blink twice Jake just tell us the truth Jake thank you for joining us Jake that's awesome that was awesome that was
00:32:31
excellent