JP Lewin

CEO Foundy: sell & acquire £100k to £15m revenue businesses via Foundy.com's first of its kind AI powered acquisition portal | You no longer need 5 separate tools and 4 advisors, Foundy has all in one portal.

22 acquisitions completed. Recent client received 4 offers in a month and sold in 9 weeks to a YC-backed buyer for a multi-7-figure cash sum. 12,000+ acquirers signed up.

My Story
After selling my first company, I realized M&A is broken. Tens of thousands spent on advisors, months wasted on tire-kickers. I built DealFlowAgent to fix it.

What I Do
I run an AI-native M&A advisory firm with a world-first conversational AI matchmaking engine. Think Boardy or JackandJill.AI but focussed on matchmaking business buyers to business sellers. 4000% higher liklihood of completing a successful deal through this method compared to a marketplace. 

How? Our AI Deal Origination Manager on the buy side, Sterling, has 15 minute conversations with acquirers to understand their unique search interests and criteria before matching them with sellers in our internal mandates or partner network and beyond. Every sell-side client gets an expert human advisory team plus a custom-trained Deal Concierge that becomes a deep expert in your business and process. Human + AI delivers investment bank-grade deal prep from start to completion.


How I Can Help
Business Owners: Thinking about selling in 1-36 months? Head to DealFlowAgent.com for a personalised list of active acquirers, then chat with our Exit Planning AI, Sage, to build your exit plan and improve your company's real valuation. 

Acquirers & Investors: Sterling is free. 15-minute conversation, then receive tailored deal flow matched to you.
M&A Advisors & Brokers: Upload your mandates and let our network find qualified acquirers.

The Vision
Give owner the highest probability of a successful exit with the right buyer
Become the default M&A infrastructure for 1m to 50m $/ £ M&A market. Relationships and real conversations can't be scraped by generic AI. Every Sterling conversation compounds into a proprietary advantage. 

Following recent traction, we've raised from an amazing group of investors including the former CTO of a fintech that scaled 0 to $1bn revenue and a term sheet from a fund with 30 + unicorns in the Partners Portfolio.

Based in London, frequently in New York. If you've made it this far, we should probably just talk. Send me a Direct Message.

Founder and CEO

Foundy has overhauled the acquisition process for tech business sellers and acquirers. We are specialists in helping founders ready their business for an exit, including preparing their data room and finding relevant acquirers. Alternatively, founders and buyers can use our platform for free on a self-serve basis if they prefer. 

Buyer accounts include representatives of large tech companies, private equity and software aggregators as well as acquisition entrepreneurs and family offices. Sellers include founders of mostly profitable online businesses in verticals such as SaaS, fintech, mobile apps, marketplaces, eCommerce, Amazon FBA, Web3 and AI but we are very much open to hearing from companies in other sectors and industries, as well as distressed businesses. 

Alongside a range of digital tools and M&A advisory services, I am helping my team to produce podcasts, tutorials and blogs with the intention of delivering helpful insights and tips to company leaders, buyers and aspiring entrepreneurs on their journey to exit 💵

Join today by creating a free and anonymous account or sign up to our newsletter on https://app.foundy.com/sign-up

Joe Lewin

Capital One just paid $5.15B for Brex.

Down 58% from the 2022 peak valuation. That's a tough outcome for late-stage investors. Here's what founders should take from this:

Brex built something real. 10,000+ enterprise customers. Integrations with 100+ platforms. A team that shipped relentlessly. That's why a bank wanted it. 

This playbook of incumbents acquiring AI native players is accelerating but here's what's shifted: it's not just about the product anymore.

Software is accessible and getting more so. What's actually valuable is entrenchment. Distribution. Brand strength. Sticky revenue.

You can build a competing product in months. You can't replicate 10 years of customer trust.

For founders: the companies getting acquired aren't the ones with the highest peak valuations. They're the ones with real traction that buyers can't build themselves.

What's the state of play with fintech and other tech market valuations in 2026? Would be good to hear what others in the space are seeing.

Joe Lewin 

Founder | DealFlowAgent.com | Acquirer x seller matchmaking and warm intros | Conversational AI M&A

Forget everything you know about PE. General Catalyst isn't just buying companies in 2026; they're building a new kind of empire that throws the old school playbook out the door

This isn't about financial engineering. It's about a fundamental rewiring of entire industries. They're not looking for well-run essential service businesses to optimize; they're looking for fragmented, low-margin service businesses to completely transform. They're not just buying your company; they're buying your industry's inefficiencies and buying vertical supply and distribution

If you own a business in one of their 70 target categories, you're not just a potential acquisition target; you're a data point in a much larger experiment. The question is, will you be the one who gets acquired, or the one who gets disrupted? The line is thinner than you think.

#AI #MandA #VentureCapital #Disruption #FutureOfWork
#DealFlowAgent

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Why Private Equity Can't Get Enough of Home Services Businesses

Private equity firms are flooding capital into home services. Here's why:

The market is fragmented. Thousands of small, independent businesses across HVAC, plumbing, electrical, and pest control. That fragmentation creates a consolidation play.

Recurring revenue is predictable. Maintenance contracts generate steady cash flow. PE loves predictability.

Essential services are recession-resistant. People need their HVAC fixed, their plumbing working, their electrical systems safe. Demand doesn't disappear in downturns.

Skilled labor shortage drives valuations up. There's a persistent shortage of qualified technicians. That scarcity benefits well-run businesses with strong teams.

The math is simple: fragmented market + recurring revenue + essential services + labor scarcity = acquisition target. If you own a home services business, you're sitting on something PE wants.

Acquirers drop hints in every call. Some are loud, some so quiet even top (human) business brokers can miss them or forget - but with M&A these mistakes can cost owners and buyers millions

After a few months with Sterling (our conversational AI at DealFlowAgent), hundreds of investment bank grade conversations later, patterns are clear.

Everyone knows the surface-level asks.

“Recurring revenue?” Sure, we all expect that. But I’ve learned to listen in for the subtle lines.

Here are the hidden buyer signals our AI never misses:

- “How many hours a week does the owner work?”
If they ask this, they want freedom, not another full-time gig.

- “What happens if their top client leaves?”
If it comes up twice, that’s a big red flag for buyer risk.

- “Are the numbers actually clean?”
Not about profit-think hidden debt, legal issues, or anything in the fine print.

- “Is there a story behind that revenue jump?”
Spikes scare buyers if the reason is unclear. “Seasonality” rarely works.

Then you get a different group of phrases, and these say “I’m interested”:

- “I can see this fitting with what we already have.”
That’s integration talk-big sign.

- “If the handover is smooth, I’d move fast.”
Now they’re thinking about whether the founder will stick around. Trust moment.

- “What could block this deal?”
Translation: let’s problem-solve together, I want to make it work.

AI picks these up before many people do. When I sold my own business, I heard “What do you do when you take a month off?” (that one always made me laugh).

Now our AI agents catches these clues before most people do. Every hint gets logged. Every pattern gets picked up. That changes the game.

We built a world's first AI native IB infrastructure that matches buyers and sellers based on real search needs and nuance criteria. For owners, we find buyers who can actually buy, and care about the legacy left behind.

Makes me think, what is the most surprising thing a buyer ever said to you in a deal?process?

Some AI-enabled service roll-ups are quietly hitting $100M in profit in under 2 years 🤯 Others go to zero. Is this the next Crypto? 

In the attached video, General Catalyst CEO Hemant Taneja talks about the $16 trillion opportunity in buying essential services and making them AI-enabled. Capital is flooding out of pure software and into this space.

But is the hype getting ahead of reality? 

More buyers are using our conversational AI, Sterling, for Deal Origination to find 1-20M revenue businesses in niches such as dental, HVAC, plumbing, and waste management. 

But a robot isn't performing a root canal or fixing an air conditioner anytime soon. These are human-in-the-loop businesses. They always will be so buyers need to be cautious about what they seek to automate post acquisition to avoid devaluing the company's brand and customer retention.

So, the playbook isn't entirely replacing humans. It's augmenting them. Automating scheduling, billing, procurement, supply chains.

The winners won't be "AI-native." They'll be "AI-enabled." Software-like margins, human-delivered service.

Even in M&A, AI finds the perfect match. A human closes the deal.

Smart people are navigating this: Alex Prokofjev and Pavel Prokofiev, ACA at RollUpEurope and affiliated funds, Dan Lifshits at Dwelly proving the model in property.

What's your take?

Overrated or Underrated? Add your thoughts below.

#MergersAndAcquisitions #AI #PrivateEquity

95% of AI implementation projects fail at Fortune 100 companies.
You don't need an AI-native company. You need an AI-native team. Then you go shopping.

The video interview from General Catalyst's CEO provides more insight.

An MIT study found most Fortune 100s tried implementing AI and called it "janky" and a waste of time.

His take: AI is still a buzzword that's genuinely hard to implement. And we're not going straight to AGI where agents do everything overnight.

So what's the move?

The hybrid approach.

Step 1: Build an AI-native team. People who were Head of Applied AI at Rippling, Scale, Stripe, Figma. Engineers who've actually deployed AI in enterprise settings.
Step 2: Incubate AI-native software with that team.
Step 3: Go acquire traditional service businesses with real customers, real revenue, real relationships.
Step 4: Merge them together.

AI-native team + traditional customer base = best revenue growth, best margin profile.

The mix of people, software, and agents will be unique to each industry. But the formula is the same. General Catalyst has companies in their portfolio that are quietly and casually generating over $100 million in EBITDA within two years of starting.

This is how you build category-defining companies. Not by slapping AI onto a legacy business. Not by building pure software with no distribution.
By combining both. 

Acquirers, if you're looking to meet owners with hidden gem companies aligned with your unique search interests, come have a conversation with our AI Deal Origination Manager.

What's your take on this hybrid model?

#AI #PrivateEquity #MergersAndAcquisitions

Homeowners across the USA and UK spent $608 billion on maintenance and improvements in 2025. That's not new construction. That's existing homes.

The aging housing stock (median US home >40 years) and the "lock-in effect" (homeowners staying put due to high interest rates) are driving continued, heavy investment in maintenance.

And here's the kicker: 87% of millennial homeowners have at least one pending repair project. 84% have postponed addressing it.

That's embedded demand. Future revenue sitting on the sidelines, waiting to be captured. Upfront fees followed by sticky maintenance and upgrades revenue.

What does this mean for home services businesses, in niches such as HVAC, fire safety, electrical, landscaping, roofing and pest control etc...? Demand is strong and getting stronger. 

Acquirers see this data too. They're buying $/£1m to 50m revenue businesses in this space, installing AI enabled workflows and systemising processes to unlock efficiencies and better customer service. This translates into more revenue, higher profit margins and a significantly higher valuation multiple within a short time period post acquisition.

If you're thinking about selling or buying a business in the next 3-24 months, you're operating in a market with massive structural demand. That's a powerful position to be in.

DataGems

Co-Founder

Erez Capital

Venture Partner

BADideas.fund

Angel Investor

Founders Capital

CADLabs

Chief Operating Officer

International Faculty of Engineering (Lodz University of Technology)

Guest Lecturer (Innovation & Innovation Management)

Booksy

Head of Product Data

Netguru

Managing Innovation department which entails:
- running the portfolio of R&D internal products and experiments
- organizing hackathons - internal and with clients
- consulting on scaling innovation across the client portfolio
- building R&D culture and stimulating internal growth of the team

Innovation Lab Manager

Theta (NZ)

Acting Practice Lead. 
A role that is known in New Zealand as Consulting Director which is a mix of:
- Technical Pre-sales
- Technical Leadership and Line Management
- Advisory

Analytics Practice Lead

Emirates Group

Portfolio Manager

Lead BI Analyst
Scrum Master - BI Enablement team

Consultant

Konrad (Co-founder & CEO of DataGems) has devoted his career to building and scaling data science teams. He's led teams that have successfully launched products in diverse sectors, including SaaS, AI, augmented reality, machine learning, advanced analytics, and web3.  He worked with top brands across four continents ranging from startups like Booksy (unicorn) to enterprises such as Emirates Airlines.

Konrad Jarocinski

The creator of Claude Code just showed his setup.

And it's surprisingly... normal.

Boris Cherny (Head of Claude Code) shared exactly how he and his team dogfood their own tool. No fancy hacks. Just workflows that actually work.

Here's what caught my attention:
- He runs 5-10 Claudes in parallel: 5 in terminal. 5-10 in browser. A few on his phone throughout the day.
- He's not waiting for one task to finish. He's running them all at once, switching between tabs, checking in when they need input.
- This is the opposite of how most people use AI coding tools. We treat them like a single assistant. Boris treats them like a distributed team.

Everything starts in Plan mode

- Shift+tab twice. Every single time.
- He goes back and forth with Claude on the plan until it's right. Then switches to auto-accept mode and Claude usually one-shots the implementation.

The insight: a good plan is more valuable than fast code generation.

CLAUDE.md is a team sport:

- The whole team contributes to a single CLAUDE.md file multiple times a week.
- Anytime Claude does something wrong, they add it to the file. "Never use enums, always prefer literal unions." Done.
- During code review, they tag @claude on PRs to update CLAUDE.md as part of the review process.
- It's their version of "compounding engineering"- every mistake becomes institutional knowledge.

The pattern I'm seeing:

- Most people optimize for speed. Boris optimizes for compounding.
- Parallel execution compounds your time.
- Good planning compounds your success rate.
- CLAUDE.md compounds your team's knowledge.

On Wednesday, I'll share the automation layer - slash commands, verification loops, and MCPs. That's where it gets really interesting.

But first: are you running AI tasks in parallel or sequentially? Most people are still doing one at a time.

#VibeCoding #AI #ClaudeCode

Fractional Chief of Staff. Chief Vibe Coder. I build what you need with AI.

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