George Eliadis did not begin his career thinking about artificial intelligence, venture capital, or building software for some of the largest home service companies in the country. As a teenager in upstate New York, he spent six summers pressure washing houses with his father, doing the kind of work that required long days in a truck, physical labor on job sites, and constant attention to whatever needed to happen next.
The business gave George an unusually early view into the operational problems that small contractors deal with every day. He has described spending two or three hours driving between jobs, which meant a significant part of the workday disappeared before another house was ever cleaned. When he finally arrived at a property, he could be standing on a ladder with a pressure washer running while a potential customer called a phone he could not hear. By the time he noticed the missed call, that homeowner might already be talking to another contractor.
Years later, George would build a company around the same kind of problem.
In June 2026, Probook announced $40 million in funding from Andreessen Horowitz and Sequoia Capital. The investment included a $34 million Series A led by Andreessen Horowitz and an earlier $6 million seed round led by Sequoia. Probook describes itself as an AI operating system for home service businesses, with a particular focus on plumbing, HVAC and electrical companies.
The distance between those two points is what makes George's story interesting. He went from helping his father run a pressure-washing business to building software designed to manage customer calls, dispatch decisions, scheduling and other workflows across home service companies with hundreds of technicians.
The idea did not appear because George sat in a classroom and decided the trades looked like a good market for artificial intelligence. It grew from watching how much time contractors lose trying to perform the work while simultaneously running the business around it.
The Business Started With George and His Dad
George's father had previously worked as a New York City police officer before an injury ended that part of his career. He later began pressure washing, and George started helping him on weekends and during the summers while he was still in school. George eventually continued doing the work while studying at the University of Pennsylvania.
Those six summers gave him experience most technology founders never get. He was not studying home service companies from the outside. He was sitting in the truck, traveling between customers and dealing with the practical limitations of a small operation where the same people selling the job were often responsible for completing it.
The logistics bothered him almost as much as the physical work. George has said that he and his father could spend two or three hours every day driving between jobs, which created an obvious ceiling on how much work the company could complete. Every unnecessary mile reduced the amount of productive time available, and every missed phone call represented another opportunity that might disappear before they had a chance to respond.
As George began studying engineering and business, he started looking at those frustrations differently. What had once felt like the normal inconvenience of running a pressure-washing business began to look like a problem software might be able to solve.
His First Idea Was Built for Pressure Washers
George's earliest attempt was close to the business he already understood.
He began exploring scheduling and routing software for pressure-washing contractors. The logic seemed straightforward. If a business could reduce the amount of time spent driving between jobs, technicians could complete more work during the same day and the owner could generate more revenue without adding another truck.
The operational problem was real, but George quickly discovered that a real problem does not always create a viable software market.
Many pressure-washing companies were still small owner-operated businesses, including the kind of operation George had worked in with his father. They might benefit from better routing, but relatively few were prepared to spend significant amounts of money on sophisticated scheduling software.
George later described this period as one of the early failures on the way to Probook. He had identified inefficiency, but he had not yet found a market where solving that inefficiency was valuable enough for customers to pay meaningful money for the solution.
That forced him to keep looking.
Painting Looked Promising, but the Problem Was Still Too Small
George eventually began working with Nolan Painting in Pennsylvania and spent time developing scheduling tools around its estimating operation.
A larger painting company seemed like a better fit because it had more employees, more appointments and more complexity than the small pressure-washing businesses he had initially approached. George could help route estimators between appointments and make their schedules more efficient.
Once he understood the business more deeply, however, he discovered another limitation.
A painting company might have only a small number of estimators moving between homes, while painting crews often remain on the same project for an entire day or several days. That meant the scheduling board did not change often enough to create the kind of difficult, constant decision-making problem George wanted to solve.
He had found a larger customer, but he still had not found the right operational challenge.
That changed when he moved into HVAC and plumbing.
HVAC and Plumbing Had the Complexity He Was Looking For
A busy HVAC or plumbing company can look completely different from a painting operation.
Dozens of technicians may be moving between homes every day. Emergency calls arrive unexpectedly. Some jobs finish early while others run long. One technician may be excellent at diagnosing complex repairs while another has a much stronger track record converting replacement opportunities.
The dispatcher has to make decisions continuously.
The question is not simply which technician is closest to the customer. The company also needs to consider skill level, availability, expected job value, location, customer needs and what other calls are waiting on the board.
George began to see that dispatch was not just a scheduling problem. It was directly connected to revenue.
Sending the wrong technician to the wrong call could reduce the chance that a homeowner received the right solution. It could increase drive time, reduce technician utilization or cause a high-value job to be delayed while somebody better suited to it was sent elsewhere.
For the first time, George had found a problem that became more valuable as the contractor became larger.
The challenge was convincing contractors to let him solve it.
Being a Young Software Founder Did Not Make Contractors Trust Him
George was still a college student when he began trying to sell his ideas to home service companies.
That created an obvious credibility problem.
Contractors who had spent decades building HVAC and plumbing businesses were not necessarily interested in changing their operations because a young software founder told them he could improve dispatch.
George has described the early years of Probook as a long period where almost nobody wanted what he was building. He tried pressure washing, moved into painting and eventually spent roughly a year and a half building for HVAC and plumbing without seeing the traction he expected.
The problem was not that he stopped believing in the market. He simply had not yet earned enough trust or found a way to prove that the software created measurable value.
His breakthrough came when one contractor finally gave him the opportunity to work inside the business instead of selling to it from the outside.
TR Miller Changed the Direction of Probook
George met leaders from TR Miller Heating, Cooling, Plumbing & Electrical, an Illinois home service company generating roughly $40 million in annual revenue.
Instead of simply trying to sell them software, George spent a summer inside the company.
He rotated through the call center, dispatch and inside sales. He took calls, worked with the board and followed up on unsold estimates. That experience gave him a much deeper understanding of what the customer journey looked like after the phone rang.
What surprised him was how manual many of the workflows still were.
TR Miller was not an unsophisticated contractor. It was a sizable company with significant revenue and established operations, yet employees were still required to coordinate complicated customer and technician decisions manually throughout the day.
For George, that changed the size of the opportunity.
If a well-run $40 million home service company still experienced these problems, then the issue was not limited to small contractors like the pressure-washing operation he grew up around.
The same inefficiencies existed at a much larger scale.
Dispatch Became the Center of the Business
George eventually became convinced that dispatch was one of the most important operational functions in a home service company.
A large contractor might have 40 technicians available and 150 potential jobs waiting. The dispatcher has to decide which technician should handle each call, when the appointment should happen and how the decision affects the rest of the board.
A traditional scheduling system can tell the dispatcher which technicians are available. What it does not necessarily understand is which technician creates the best economic outcome for each opportunity.
One technician might have a stronger conversion rate on replacement calls. Another might be better with complex diagnostic work. Sending either one to the wrong customer could affect revenue even if both technicians technically have enough time in the schedule.
That is the problem Probook decided to attack first.
Andreessen Horowitz later described dispatch as the central decision in a home service business because technician utilization, revenue and customer experience all depend heavily on how those decisions are made. Probook built around that layer before expanding into other parts of the customer journey such as intake, customer messaging, data cleanup and outbound communication.
That approach made the company very different from many of the first AI products arriving in the trades.
AI Was Already Flooding Home Services
By the time Probook began gaining traction, contractors were already being offered an enormous number of AI products.
Some vendors focused on answering phone calls. Others offered chatbots, automated follow-up, customer messaging or outbound sales tools.
George believed the technology itself was useful, but he saw another problem developing.
A contractor could purchase one product to answer calls, another to follow up on estimates, another to communicate with customers and yet another to help with scheduling. Instead of reducing complexity, AI could create an additional collection of vendors that the company still had to manage.
Probook's argument was that these workflows should be connected.
The same system that understands the initial customer call should also understand how the job is categorized, which technician is best suited to it, what happened during the appointment and what follow-up should happen afterward.
That is why the company describes itself as an operating system rather than simply an AI receptionist.
The goal is to connect the customer journey from the initial call through the technician arriving at the home, while allowing employees to focus on unusual situations that still require human judgment.
The Company Struggled for Years Before Finding Product-Market Fit
The $40 million funding announcement makes Probook's rise look extremely fast.
George tells the earlier part of the story very differently.
He has said the company spent roughly two and a half years struggling to find true product-market fit. Pressure washing had failed as a market. Painting was not the right fit either. Even after moving into HVAC and plumbing, the team spent a long period building and testing without creating the traction they expected.
One of the biggest problems was how George was validating the product.
He had worked in the trades and believed the best way to prove Probook was useful was to show contractors exactly how it worked inside their dispatch operations, often by allowing them to use the product without requiring much financial commitment.
His co-founders challenged that approach.
They argued that contractors agreeing to use free software did not prove that the product was valuable enough to support a serious company.
The better question was whether customers were actually willing to pay for it.
Once the team began testing demand from that perspective, George says the results changed dramatically. After roughly two and a half years of struggling, Probook crossed $1 million in annual recurring revenue within about four and a half months.
That period is important because it shows how far Probook was from an overnight success.
George had the industry experience and the technical idea, but the company still had to learn what customers valued enough to pay for.
The Founding Team Combined Trades Experience With Engineering
George eventually built Probook with co-founders Lewis Zhang and Ben Cervantez.
Ben also had a direct connection to the trades, having grown up helping his father with plumbing work in San Francisco. Lewis brought a different kind of background through his technical education in electrical engineering and computer science at Berkeley.
That combination became central to the way Probook presented itself.
The company was not claiming to understand contractors simply because the home service market looked attractive to investors. Two of its founders had direct experience around the work, while the technical team could build the kind of complex AI systems required to automate decisions across large operations.
That combination matters more than it might appear.
Some people understand the trades deeply but do not know how to build sophisticated software.
Others can build sophisticated software but have very little understanding of how a plumbing, HVAC or electrical business actually makes money.
Probook wanted to combine both perspectives.
The Early Customer Results Got Investors' Attention
As Probook moved into larger home service companies, it began reporting much more substantial operating results.
Andreessen Horowitz says Summers Plumbing, Heating & Cooling deployed Probook across 14 locations and 260 technicians. During the first month, the system booked 2,542 jobs without a human employee manually handling the bookings.
Del-Air reportedly increased productivity from roughly 10 technicians per dispatcher to 22. Probook has also reported that other customers improved revenue per job while operating with leaner teams.
These results come from Probook and its investors rather than independently audited financial records, so they should be treated as company-reported performance.
The underlying business case is still important.
A large contractor does not necessarily need AI to replace everyone in the office for the technology to produce value.
If the same dispatcher can effectively manage twice as many technicians, or if fewer customer calls are lost before booking, the economics change quickly.
A small percentage improvement across a company operating hundreds of calls every day can create far more value than saving a few minutes writing emails.
George Stayed Extremely Close to the Customers
Probook's growth also came with a very hands-on sales strategy.
Fortune reported that George remained the company's only salesperson until February 2026, even after Probook had started gaining significant traction.
He spent extensive time with the contractors using the software, including staying with customers and attending important personal events such as weddings.
The approach made sense because Probook was asking customers to trust software with important operational decisions.
A company can tolerate a marketing tool being slightly wrong.
Dispatch is different.
If the software sends the wrong technicians to the wrong customers or misinterprets what the business prioritizes, the impact can spread across the entire day's schedule.
George and his team therefore spent time deploying Probook directly with customer teams rather than treating implementation as a remote handoff.
That helped the company understand why contractors made certain decisions instead of simply trying to automate the visible workflow.
Sequoia Invested First
Sequoia Capital eventually led Probook's $6 million seed round.
The firm pointed directly to George's experience in the trades when explaining why it believed the company was different.
Sequoia partner Konstantine Buhler argued that many founders trying to build technology for tradespeople have never actually worked in that environment, while George had spent years seeing the problems himself.
That experience became part of the investment thesis because Probook was entering a market that had suddenly become extremely attractive to both technology companies and private equity firms.
Large investors had already spent years acquiring plumbing, HVAC and electrical businesses across the United States. Those companies frequently operate across several branches with hundreds of technicians and thousands of customer interactions.
At that scale, improvements in scheduling, booking, technician utilization or average job revenue can become financially significant very quickly.
Probook was trying to insert itself directly into those decisions.
Andreessen Horowitz Then Led a $34 Million Series A
The next major step came in June 2026.
Andreessen Horowitz led a $34 million Series A, with Sequoia also participating. Combined with the earlier seed round, Probook had raised $40 million.
George was still only 24 years old.
A few years earlier, he had been spending his summers pressure washing houses with his father.
The funding is a dramatic part of the story, but it is important to understand what the number means.
Probook did not earn $40 million in profit or generate $40 million in sales from its software. The company raised $40 million from investors who believe its technology could eventually become much more valuable.
Funding, revenue and valuation are very different numbers.
What the investment does show is how seriously major technology investors are beginning to take AI inside the trades.
Home Services Became a Serious AI Market
For years, the trades were often treated as late adopters of technology.
That reputation is disappearing.
Modern home service companies already use sophisticated software for customer management, scheduling, dispatch, financing, payments, call tracking and marketing attribution.
Artificial intelligence adds a new layer because software can now perform work that previously required somebody in the office to read information, make a decision and take an action.
A missed call can trigger an automated response.
An unsold estimate can receive follow-up.
An incoming customer can be categorized before a dispatcher sees the job.
Technician availability can be considered alongside skill level and expected revenue.
The technology can potentially influence thousands of decisions that once required somebody in the office to handle each one manually.
That is why investors are spending heavily in this part of the market.
The opportunity is not simply helping a plumber write a social media caption.
It is changing the way the entire company operates.
ServiceTitan Makes the Opportunity More Complicated
Probook is also building in a market where ServiceTitan already has enormous influence.
ServiceTitan is a major operating platform for home service companies and has developed its own AI capabilities, including scheduling and dispatch tools.
For now, Probook integrates with ServiceTitan and positions the products as complementary rather than direct replacements. Fortune noted, however, that the relationship creates an obvious strategic question because both companies are investing heavily in technology around home service operations.
That competitive environment raises the standard for Probook.
The company cannot succeed simply by offering another AI feature.
It has to create enough value around dispatch and customer operations that large contractors believe using it alongside their existing systems materially improves the business.
The deeper Probook becomes involved in the operation, the greater both the opportunity and the risk.
A mistake in an AI-generated social media post is inconvenient.
A mistake affecting hundreds of technician assignments can become expensive.
The Original Pressure-Washing Problem Never Really Disappeared
The companies using Probook today may have hundreds of technicians, multiple locations and sophisticated software stacks, but the original problem George noticed while working with his father is still there.
A home service company has a limited amount of time.
Someone has to answer the customer.
Someone has to schedule the call.
Someone has to decide which technician should go.
Someone has to update the homeowner when the schedule changes.
Someone has to follow up when the estimate is not sold.
When George and his father were pressure washing houses, two people were trying to manage those responsibilities while also doing the physical work.
In a $50 million HVAC company, the same basic problem exists on a much larger scale.
There may be dozens of office employees trying to coordinate hundreds of technicians and thousands of customer interactions.
George's bet is that much of that repetitive work can eventually be handled by software.
The Biggest AI Opportunity May Be Inside the Operation
Most contractors first encounter artificial intelligence through marketing.
They use ChatGPT to write an ad, create an email, draft website copy or generate social media ideas.
Those tools are useful, but George's story points toward a much larger opportunity.
AI can potentially affect how the business itself runs.
It can influence how quickly a lead is answered, how an appointment is booked, which technician receives the call, how many technicians a dispatcher can manage and whether a customer receives follow-up without an employee remembering to send it manually.
For a small contractor, improving one of those processes may save several hours each week.
For a company operating across 10 or 20 locations, the same improvement can affect thousands of jobs.
That difference in scale explains why investors are willing to put large amounts of money behind technology targeting the trades.
AI Still Needs a Business Worth Optimizing
George's story also contains an important warning for contractors who assume buying AI automatically improves the company.
Software needs something useful to optimize.
A contractor still has to understand basic business metrics such as booking rate, average ticket, close rate, technician capacity and the value of different types of calls.
If the company has no idea which technicians perform best on different jobs, AI cannot magically create that knowledge without enough information.
The technology becomes far more valuable once the business already understands its own economics.
That means the starting point should not be asking which AI tool is popular.
The starting point should be identifying where the company repeatedly loses time, money or opportunities.
Once the problem is clear, technology can be evaluated against it.
Six Summers in a Truck Became the Beginning of the Product
It would be easy to describe George Eliadis's story as a simple transformation from pressure washer to AI founder.
That misses most of what actually happened.
The pressure-washing business taught him how much time small contractors lose to logistics. His first attempt to build software for that market taught him that a real problem is not always a valuable enough market. Painting showed him that a larger contractor does not necessarily have a complex enough scheduling problem.
HVAC and plumbing finally gave him the right combination of scale and operational difficulty.
Working inside TR Miller helped him understand how those problems actually looked inside a sophisticated company. His co-founders pushed him to validate whether customers would truly pay for the product. Years of experimentation eventually turned into traction, recurring revenue and relationships with large home service brands.
Only after all of that did the major funding arrive.
The six summers with his father were not a cute detail added to the story afterward.
They were where George first saw the problem.
The Lesson for Contractors Is Bigger Than Probook
Most contractors reading George's story are not going to build an AI startup or raise $40 million from venture capital firms.
That is not the useful lesson.
The useful lesson is that many of the largest opportunities inside a business begin as problems the owner has learned to tolerate.
A contractor may accept that calls get missed while technicians are busy.
They may accept that dispatch requires several people constantly adjusting the board.
They may accept that unsold estimates receive inconsistent follow-up or that office employees repeatedly move information between systems.
After enough years, those inefficiencies begin to feel normal.
George's experience shows why they are worth questioning.
The same frustration that once looked like an ordinary part of operating a pressure-washing business eventually became the foundation for a software company backed by some of the largest technology investors in the world.
For contractors, the right question is not where AI can be added because everyone is talking about it.
The better question is where the business keeps performing repetitive work, losing opportunities or spending money because the current system was simply accepted as normal.
That is where the most useful technology usually starts.
From Missing Calls on a Ladder to Building AI for the Trades
When George Eliadis was pressure washing houses with his father, missing a phone call could mean losing the next job.
Today, Probook is trying to solve the same problem across companies operating hundreds of technicians and multiple locations.
The scale is completely different, but the economic principle has barely changed.
Every missed customer, unnecessary mile, poor technician assignment or repetitive office task consumes resources that could have been used more productively.
George and his co-founders are betting that artificial intelligence can handle enough of those decisions to make home service businesses significantly more efficient.
Investors have now put $40 million behind that idea.
Whether Probook ultimately becomes the operating system George believes the industry needs will depend on what happens over the next several years.
What is already clear is how the idea started.
Before the venture capital, before the engineering team and before the AI platform, George spent six summers in a pressure-washing truck learning how difficult it can be to perform the work and run the business at the same time.
Years later, he turned that frustration into the problem he decided to solve.
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