#118: A Brave New World, The Story of Pipedreams, Customers Needed To Achieve $10M in ARR
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Alright, let’s get to it…
One ‘How To’:
A Brave New World
Eli Dukes (a great student/writer of the vSaaS game) and I (Luke Sophinos) have been jamming lately and have been a bit befuddled by one thing:
AI-driven M&A feels incredibly obvious as a long term opportunity, yet while the X posts are abuzz with the opportunity, there’s a lot of uncertainty around the strategy in the financial markets.
The History of B2B SaaS & How We Got Here
If you zoom out and look at the last two decades of b2b software we’ve gone through very interesting waves…
Wave #1: Mainframe (1960’s to Late 1980’s):
Large, centralized mainframe computers that ran mission-critical applications for businesses. Think batch processing, proprietary systems, high costs, and specialized technical skills being required. Notable Companies in this phase included IBM, Unisys, Burroughs, Honeywell, and Control Data Corporation.
Wave #2: Client Server & PC (Late 1980s to Late 1990s)
With the advent of personal computers (PCs) and client-server architecture, businesses began adopting decentralized computing models. Distributed computing, graphical user interfaces (GUIs), local area networks (LANs), and the rise of workplace productivity software. Notable companies include Microsoft (Windows, Office), Oracle, Novell, Lotus, and Borland were prominent in this era.
Wave #3: Horizontal SaaS (Mid 1990s to Present):
Horizontal software refers to applications that can be used across any industry and business functions, such as enterprise resource planning (ERP), customer relationship management (CRM), and supply chain management (SCM) systems. Notable companies include SAP, Oracle, Microsoft, Salesforce, and Workday are major providers of horizontal software solutions.
Wave #4 Vertical SaaS (Late 1990s to Present):
Vertical software is designed to address the specific needs and requirements of a particular industry or sector, such as healthcare, finance, retail, or manufacturing. Software vendors deploy tailored tools and deep domain expertise. Notable companies include Toast (Restaurants), ServiceTitan (Field Services), Veeva (Life Sciences), Epic Systems (Healthcare), Procore (Construction), Instructure (Higher Ed). Embedded payments, ads, and other plays came out in early-to-mid 2010s and drastically increased TAM and revenue for vertical SaaS players.
So What Comes Next?
#1. Vertical AI
Vertical AI is a relatively new term that refers to the application of artificial intelligence (AI) technologies and solutions tailored for specific industries or vertical markets. This approach contrasts with horizontal AI, which focuses on developing general-purpose AI solutions that can be applied across various domains. Example companies include Vertical AI would be Harvey for Lawyers, AxionRay for Manufacturing, Sixfold for Insurance Underwriting, MagicSchool for Education. Where-as horizontal AI would be Customer Service AI or SDR AI.
#2. Venture Buy Outs
When an early-stage company builds a game changing product for a specific industry, buys companies in that specific vertical, and implements their game changing technology that results in the end business dramatically increasing margins. From there, they run an M&A playbook at venture-scale.
VBO’s sit somewhere between Private Equity and traditional VC. Private Equity backed services businesses add in a “veneer” of tech-enablement. The reality is they are not technology businesses. They are financial engineering to realize margin improvement and proclaim that tech is making a big impact when it’s really not. Early example companies include Metropolis (Parking Lots), Cabana (Pool Cleaning), LedgerUp (Accounting), and Roofer.com (Roofing Home Service Businesses).
#3. The End Company That The SaaS Is Servicing Becomes THE Tech Company
If you’ve been paying attention to the vertical AI wave, you may have noticed that nearly every vertical AI company is doing a lot of “forward-deployed” work. This is no coincidence. AI is inherently performing more aspects of the core work for a business. Every company believes that their specific version of the work is important and differentiated enough and so naturally, they ask for their AI solutions to look more like the work their specific company performs vs. what it looks like in a Platonic state across the industry. And in most cases, the AI companies end up instantiating a mini-revolution inside the companies they work with. After all, every AI company’s revenue is predicated on meaningful transforming the operations of the companies they work with.
Today, it looks a lot like the homebuilding industry.
Companies are increasingly wanting “custom houses” - Vertical SaaS or Vertical AI solutions may be scaffolded for the industry but company A wants an open kitchen concept while company B wants a sauna installed.
Founders today are both architects and builders managing tons of different projects at once.
Both parties see the payoff! The tech today dramatically improves margins and will continue to do so. But the closer it is to a company’s core operations, the more they want to “own” the blueprints and the buildout. After all, they are the ones responsible for delivering their goods or services. They may not have the requisite expertise, but there is a latent desire to look more like a technology company. And what better way to do this in principle than to acquire companies that want to be technology companies and actually make them so?
What Has To Get Figured Out To Unlock The Next Evolution
But this has taken hold quite yet, we believe there are a few key things that MUST get figured out for this next phase to take hold.
The market must price VBO Services Companies above Traditional Services Businesses & PE Backed Services Roll Ups
The primary gap in the number of theoretically possible VBOs is financial. Here’s the big problem:
There is currently no public proof that VBO companies are capable of multiple expansion.
Without this proof, VBOs remain the single most contrarian play in the financing ecosystem today.
Here’s why:
M&A typically works by buying companies, improving their EBITDA, and getting priced at a higher multiple than what you paid for. Rollups work by pursuing the same strategy but instead taking perceived riskier (smaller) assets and combining them into one larger company with more “synergies” across the business. If you successfully run these playbooks, there is a natural multiple expansion. You may acquire a services business at 2x and subsequently sell for 8x EBITDA if you are a sophisticated operator. This sets the market floor for a successful acquisition strategy.
VC firms are split on the strategy.
You may expect VC firms to be taking advantage of the underlying contrarian bets here. And there is certainly a class of investors doing so. However, contrarian bets usually require unlocking capital incrementally. Go prove it out with a small to midsize amount of money and then subsequently prove it out with a larger capital raise.
This is the major problem today.
In our view, to prove out at a VBO strategy requires a minimum of $20-30m dollars at the seed stage. Anything less and you are left without enough funding to prove out the scale of technology improvements on the core operations of the business. Not many founders can raise $20M for their seed-stage business. The key limitation here is actually not R&D. You can certainly prove efficiency gains with your technology. But if you are buying smaller assets, you are most likely going to be concentrated on growing revenue inside the business you buy (and the first move in an AI-enabled company will never be to automate revenue functions). It will suddenly be unclear how much of your growth is related to your technology vs. simply bringing in better operations. This suddenly looks a lot more like PE than VBO and your next capital raise will be priced as such. For this reason, you need to buy a big enough asset to prove out the full EBITDA impact of your technology in a business operating at scale. Only very limited VCs are comfortable underwriting that bet today.
A defined company structure that can support physical asset components w/o the overhang.
For a long time, real estate has had the notion of an opco/propco. Operations company handles the… operations, the propco owns the assets. This is also due to financial markets: certain investors want exposure to the asset-light parts of operations, others want exposure to the actual assets.
I’ll make a bold statement: AI companies probably don’t want asset exposure. If it’s all about multiples, assets will be a drag upon it. This means that in certain industries, company structures may need to get creative and resort to opco/propco structures to capture the full operational improvements from the technology. Or even figure out ways to divest assets at acquisition time. This can be as simple as converting an owner-occupied commercial real estate building into an operating lease, but can quickly grow far more complex.
On the other hand, many VC’s will just say they only invest in Delaware C-Corps without complex structures. That’s the box they are use to. That’s the box that they told their LP’s they were pursuing.
The key lesson? There isn’t a consensus answer on what to do yet.
You will need a strategy you believe in around this if you are doing acquisitions — I personally believe it’s probably starting out as a Delaware C-Corp and being open to moving to an Op-Co/Prop-Co down the road.
This will also mean that founders may need to get more creative around “tranching” capital between different investor types. We will plan on sharing more specifics around this in pieces to come.
Funds that are created that understand the above and underwrite accordingly
Lastly, a new crop of funds will need to rise. We see opportunities both in the private credit markets as well as traditional venture ones.
Private credit has exploded over recent years. Most of the private credit today chases asset-based financing or traditional corporate credit. But credit markets overtime inherently will need to specialize to gain yield (this is exactly what is playing out in the real estate market with specialized boutique operators). Once the playbook has been proven out with known multiple expansion from technology, it will make sense for private credit funds to get involved with providing more capital to founders a bit earlier in the lifecycle of the company.
And of course, we need venture firms dedicated to this concept. Ultimately, this is still a non-consensus play in the financial markets. Venture firms here will not only need to provide the capital, but sincerely advocate for their portfolio companies performing this strategy at subsequent capital raises to unlock debt and equity financings.
In Closing…
VBOs remain a significant yet contrarian play awaiting both new financial innovations and founders with the appetite to go in and do the hard work of transforming companies into tech-enabled services.
The upside is increasingly obvious with every passing model improvement and new design pattern.
But so long as the bottleneck remains purely capital related and investors wait to see how AI plays out, the opportunity today remains limited.
One Quick Question:
One Biz Story:
The Story of PipeDreams
An AI plumbing company? Yup, you heard that right...
And the founder just raised $25M to continue his acquisition spree...
Let's dive in ↓
Meet PipeDreams - an AI first roll-up founded in 2021 by Dan Laufer, who previously led growth and product marketing at Nextdoor.
His inspiration stemmed from observing high usage of Nextdoor for finding HVAC providers and identifying gaps in consumer experience.
Laufer also notes the "silver tsunami" trend, where many baby boomer business owners are looking to retire.
The company's mission is to acquire these businesses, integrate AI for scheduling and marketing, and allow owners to retire while preserving employees, names, and brands.
PipeDreams' first acquisition was Efficient Air Service, based in the Bay Area, in 2022, serving as a test case for their roll-up strategy.
They have since acquired 9 companies, operating in markets like San Francisco, Tucson, and Denver, with plans for further expansion.
This approach aligns with traditional private equity roll-up strategies but is enhanced by a startup's agility and tech focus.
PipeDreams offers a comprehensive technology stack.
This includes:
Scheduling & Operations
Marketing Automation
Data Analytics
Their AI platform also matches technicians' skill sets to projects, enhancing customer experiences, resulting in 91% 5-star reviews online.
PipeDreams supports acquired companies in customer acquisition through advanced digital marketing.Traditional HVAC companies are not typically digital marketing gurus.
Their systems shift businesses from analog to digital-first, using data to optimize campaigns.
The cost to acquire HVAC companies varies, but PipeDreams leverages a $15 million debt facility + a significant portion of equity raised specifically for acquisitions. Given they've acquired 9 companies, we can assume the average cost per acquisition is approximately ~$1.7M.
Industry benchmarks suggest small HVAC businesses are valued at 2 times seller's discretionary earnings up to $500K with larger companies fetching higher multiples (e.g., 2.5–3 times for $500K–$1M profit).
Thus, acquisition costs likely range from $1 million to $2 million.
Exact customer numbers aren't publicly disclosed, but with each company likely serving ~1K customers annually (estimate based on industry averages), they likely serve around ~10K customers / year
PipeDreams' revenue isn't publicly disclosed, but given their 9 acquisitions, each generating a minimum of $2.5M annually, total revenue is likely in the in the tens of millions.
Their claim of driving 100% growth via their tech system in 24 months is EXCEPTIONAL.
In March 2024, PipeDreams raised $25M in Series A funding, led by Canvas Ventures and Plural, with additional investments from Tony Xu (DoorDash founder) and Thomas Layton (former OpenTable CEO & Upwork Chairman).
This round brought total equity funding to $39 million.
PipeDreams' future looks promising, given the massive home services market and the 114K HVAC companies to go after. If their tech stack can really double these businesses in 2 years, that's something I'd put my money behind.
Excited to see this one play out!
One ‘How-To’:
Customers Needed To Achieve $10M in ARR
$1K ACV -------> 10,000 logos
$5K ACV -------> 2,000 logos
$25K ACV -------> 400 logos
$50K ACV -------> 200 logos
$100K ACV -------> 100 logos
Have a product or service that would be great for our audience of vertical SaaS founders/operators/investors? Reply to this email or shoot us a note at ls@lukesophinos.com
This is really timely and useful. I'm currently building an AI first voice agent that enables trades businesses in the beauty and home services sector to optimize revenue and operations.