Probook raises $40 million by putting AI at the dispatch board

Why it matters

Probook shows where vertical AI funding is moving: away from surface-level chat tools and toward workflow control points where software can change labor, revenue and margins.

George Eliadis has raised $40 million for Probook, a New York startup that wants to make AI the operating layer for plumbing, HVAC and electrical contractors, according to a Forbes column published Thursday.

The cleaner version of the financing is not one new $40 million round. Probook announced $40 million in total funding on June 23: a $34 million Series A led by Andreessen Horowitz and a previously raised $6 million seed led by Sequoia Capital, with Sequoia also joining the Series A, according to the company's announcement republished by ADVFN. Probook did not disclose a valuation.

The financing is a founder story first. Eliadis, Probook's 24-year-old co-founder and CEO, has been selling investors and contractors on a problem he says he first met directly: missed calls while pressure washing houses in upstate New York, a story recounted by Forbes. He later spent time inside TR Miller, a $40 million HVAC, plumbing and electrical shop in Illinois that became Probook's first customer, where the same missed-call problem showed up as an operating bottleneck across a much larger business.

That background matters because Probook is not pitching generic AI for small business. Eliadis and co-founders Ben Cervantez and Lewis Zhang are aiming at the dispatch board, the daily command center where home-service operators decide which technician goes to which job, in what order, with what customer history and expected ticket value. Penn Venture Lab listed Probook as a 2024 Startup Challenge finalist founded by Eliadis, a University of Pennsylvania M&T '24 student, and Cervantez, M&T '25, and described the product as home-services dispatch automation for HVAC, plumbing and electrical companies that plugs into ServiceTitan and matches technicians to jobs using historical data and routing optimization.

The round is really a bet on the operating seat

Forbes framed the investment as Sequoia and a16z paying for a plumbing dispatch seat. That is the right way to read it. Dispatch looks like scheduling from the outside. Inside a home-services company, it is where utilization, routing, conversion, customer experience and technician performance converge.

That is why Probook's wedge is narrower, and potentially more valuable, than another AI phone agent. On its site, Probook says it captures voice calls and web leads, cleans bookings with history checks, forecasts ETA and revenue, fills the board through outbounding, and automates 90% of customer chats. But the product is built around dispatch rather than bolted onto the edge of the funnel.

a16z makes the same argument in its investment post: most AI tools for trades businesses cluster around voice agents, chat widgets and follow-up bots, while Probook starts with dispatch and then expands into intake, customer messaging, data cleaning and outbound. That ordering is the pitch: own the hard decision layer first, then use that context to automate the rest of the front office.

The early customer metrics are strong, but they are still mostly company-supplied and should be read that way. Probook says Del-Air consolidated dispatch across eight locations, moving from 22 dispatchers to 10 while handling more than 15,000 calls per month as a front-line customer service representative. Probook says Anthony, a TurnPoint Services business, reduced dispatchers from 16 to 8 and increased average ticket by 20%. It says Cardinal, part of Redwood Services, reached an 82% true booking rate and a 20%+ average-ticket increase. Its customer outcomes page details these and other results.

Forbes also cites an Indiana operator that, with 14 locations and 260 technicians on the platform, booked 2,542 jobs in its first month with zero human intervention, the kind of vertical-AI metric investors want.

Private equity created the opening

The timing is not accidental. Home services has become a private-equity consolidation target because the market is large, fragmented and operationally improvable. McKinsey estimated in February that U.S. home-services spending is approximately $700 billion, that many subsectors remain highly fragmented, and that the average operator can find more than 500 basis points of margin improvement or the equivalent through growth by transforming operations.

That is the context for Probook's pitch to roll-up platforms. A contractor that owns one shop can survive with a dispatcher who knows every technician by memory. A platform that has bought 10 local businesses cannot. The more locations a platform adds, the more valuable a common dispatch layer becomes, because it standardizes how jobs are routed, how call data is captured, how customer updates are sent and how technician performance is used.

Probook is selling into that pressure. The company's announcement names customers including TurnPoint Services, Master Trades Group, Del-Air, Peterman Brothers and Sila Services. The announcement quotes Chad Peterman, CEO of Peterman Brothers, saying Probook helped centralize dispatch across 11 markets and 200 technicians without adding overhead.

That is also why investors are paying attention before Probook has disclosed revenue, pricing or gross margin. Vertical AI companies are trying to become the workflow owner before incumbents can add enough automation to protect the account. In home services, the account is often already running on a field-service management system. Probook's own Penn Venture Lab description said it plugs into ServiceTitan, which makes Probook an overlay rather than a rip-and-replace system.

ServiceTitan is partner, platform and threat

The strategic tension is ServiceTitan. Probook can benefit from integrating into the systems contractors already use, but the incumbent is not ignoring the same workflow. ServiceTitan's Dispatch Pro markets AI-driven job assignment recommendations based on technician skill, location and performance, and says it uses historical data and Titan Intelligence to predict job value. A ServiceTitan help page says Dispatch Pro considers predicted job value, prioritization, technician performance and estimated drive time, then simulates scenarios to find the most profitable board (documentation).

That overlap is direct. Probook's opportunity is to move faster, configure in person, and win operator trust in messy multi-location environments. ServiceTitan's advantage is distribution, data gravity and the fact that many contractors already live inside its workflow.

The broader competitive field is also waking up. Housecall Pro announced a May platform redesign with route-based scheduling and an AI preview. Avoca, another AI startup targeting the services economy, announced more than $125 million in funding at a $1 billion valuation in April, though its emphasis is more front-office voice and customer interaction than dispatch control.

That makes Probook's positioning clear. Eliadis is not trying to convince trades operators that AI exists. He is trying to convince them that the winning AI vendor is the one trusted with the board.

What the capital buys

In this market, deployment quality is part of the product. Probook says its team deploys in person, configures alongside customer teams and stays accountable for outcomes. The company is selling automation into businesses where a missed job, misrouted technician or bad customer handoff has immediate revenue consequences.

The unresolved question is whether Probook can turn founder-led intensity into repeatable software economics. That is an asset at seed and Series A. At scale, it becomes the test: can Probook keep the trade-specific trust while selling into hundreds of branches and increasingly sophisticated platform buyers?

The $40 million answer from a16z and Sequoia is that the dispatch board is worth fighting for. Eliadis got there from missed calls on a ladder. The larger bet is that the same missed-call, wrong-tech, underfilled-board problem is not a small-business nuisance. It is the data layer hiding inside a $700 billion services market.