Top Founders

How do you go from a Chrome extension with no sales team to $15M in revenue in five years, while raising less money than most startups spend in their first year?
David Chevalier is the co-founder and CEO of Surfe, the leading CRM enrichment and waterfall data platform for B2B sales teams. He bootstrapped for two years, grew to $1.5M purely through HubSpot and Pipedrive marketplace rankings, and has never taken a dollar of personal secondary despite being six years into the company. Today Surfe processes 50 million data points per year and is the third partner inside HubSpot's AI prospecting agent next to ZoomInfo and Apollo.
You'll learn:
How Surfe got to $1.5M in revenue with zero salespeople by becoming the number one app in HubSpot and Pipedrive marketplaces
The waterfall enrichment model that aggregates 15 data providers and why building it at scale is much harder than it looks
Why a third of their $15M revenue now comes from API usage and credits rather than seat licenses
How David revealed his company revenue publicly for the first time ever on this show
The Google partnership that started three and a half years ago and helped Surfe build the waterfall before the market even knew what it was
Why their largest customer now pays over $1 million per year and how many more are approaching that threshold
What happened when David tried to hire salespeople before the product was ready, and how many failed hires it took to find their CCO Eric
How Surfe doubled from $9M to $15M in one year with 20 AEs each carrying $700 to $800K in quota
Why 40% of their revenue comes from the US despite being founded in Paris and what it took to make that happen
What David would do differently if he could go back and negotiate secondary at his pre-Series A round
Connect:
YouTube: youtube.com/@NathanLatkawatch
Surfe: surfe.com
Founderpath: founderpath.com

How do you build a $16.5M vertical SaaS company with 24% EBITDA margins with zero paid acquisition, zero outside funding, and your wife as co-founder?
Rohit Garg is the co-founder and CEO of Practice by Numbers, an all-in-one dental practice management platform serving 1,300 customers across 2,000 locations. He started building it in 2015 because his wife is a dentist and he was the one running SQL queries to answer her business questions. Today they are bootstrapped, profitable, and sitting on $2 billion in untouched payment GMV from their existing customer base.
You'll learn:
Why Rohit built the entire platform by sweat equity while working a full-time job at Philips Healthcare
How Practice by Numbers went from $2M in 2021 to $16.5M in 2026 without spending a dollar on paid ads
Why their customers generate almost 2x the national average in dental practice revenue — and why that drives retention without any loyalty program
The $2 billion in payment GMV sitting in their system right now that they have not started converting yet
Why Henry Schein and Patterson, who own the biggest competitors, simply cannot move fast enough to build what Practice by Numbers has built
How 100% inbound word of mouth growth leads to 22 to 24% EBITDA margins at $12.5M in revenue
The AI receptionist and agentic workflow roadmap that will let dental office managers run the entire practice without touching a screen
What Rohit actually said when Nathan asked if he would sell for $180M all cash to the company that owns Dentrix
Why COVID cut the company at its knees in 2020 and what it took to relaunch and 8x revenue in five years
The vision for $100M in revenue within 10 years and why Rohit thinks it will happen faster than expected
Connect:
YouTube: youtube.com/@NathanLatkawatch
Practice by Numbers: practicenumbers.com
Founderpath: founderpath.com

How do you build a $10M business by teaching robots to write handwritten notes with real pens, and do it with zero outside investment for 12 straight years?
David Wachs sold his text message marketing company for eight figures in 2012, started Handwrytten the next day, and has bootstrapped it to 200 custom-built robots in a Phoenix facility sending 350,000 notes per month. He owns 100% of the company, took $350K in profit last year, and is targeting $10 to $11M in revenue this year.
You'll learn:
Why David thinks physical CapEx is now a competitive moat in the AI era, and why he is glad he can't be vibe coded away in a weekend
How Handwrytten went from $1M in 2018 to $9.4M in 2024 without raising a single dollar
The veterinarian euthanasia franchise that has been sending 80,000 robot-written notes per quarter for 8 straight years
Why a $5 Google ad click from a realtor generates only 20 cents in contribution margin and what that forced them to do instead
How they built a paper feed system that can write on a stuffed envelope without mismatching a single card across hundreds of thousands of sends
The robot leasing model: 30 units in the field at $1,000 to $1,250 per robot per month going to 3PL facilities and swag companies
How integrations with HubSpot, Shopify, Claude MCP, Zapier, and Salesforce turned Handwrytten into a fully automated marketing channel
Why David would sell for $100M today and what roll-up strategy Nathan pitched him live on camera
The SEO playbook that drives 40,000 organic clicks per month with zero agency spend and one in-house writer
What it actually costs to build a robot when you manufacture them yourself in Tempe, Arizona
Connect:
YouTube: youtube.com/@NathanLatkawatch
Handwrytten: handwrytten.com
Founderpath: founderpath.com

How do you go from a pricing experiment inside a failing product to $3.6 million in annual revenue with 10,000 customers — in under two years and with zero paid marketing?
Eugene Cheah is the co-founder and CEO of Featherless.ai, the largest open source LLM inference provider on Hugging Face. He co-created RWKV, the first attention-free AI architecture under the Linux Foundation, and today runs a 27-person team serving customers that pay anywhere from $25 a month to $2 million a year.
You'll learn:
Why Featherless started as an accident — a pricing experiment that outperformed the original company within days
How they grew to 10,000 customers with zero paid marketing using only Reddit posts to AI communities
The enterprise sales motion that closes $1 to $2 million per year contracts by showing startups how to cut their OpenAI or Anthropic bills in half
Why supporting 6,700 models versus competitors' 100 is the moat — and why no one else is doing it
How the RWKV architecture has the potential to reduce AI inference costs by over 1,000x compared to today's transformer models
Why the bottom 50% of AI model usage — the fine-tuned, niche, non-English models — is where the real money is hiding
What happened when servers caught fire from user growth and the team had to add capacity faster than they could hire
How a $20 million Series A in December 2025 finally gave them enough server capacity to breathe
Why Eugene believes AI models today are massively over-parameterized — and what a human brain tells us about where efficiency is actually going
The refund guarantee Eugene made live on camera and what it says about their confidence in the product
Connect:
YouTube: youtube.com/@NathanLatkawatch
Featherless: featherless.ai
Founderpath: founderpath.com

How do you build a $15M revenue business by teaching autonomous drones to find missing sneakers in warehouses, and get customers to more than double their spend every single year?
Sankalp Arora is the founder and CEO of Gather AI, a physical AI company that uses autonomous drones and computer vision to track inventory in real time across warehouses. He holds a PhD in robotics from Carnegie Mellon, built the world's first safe autonomous helicopter for DARPA, and today has 30 to 40 customers paying an average of $500K per year with net revenue retention of 170%.
You'll learn:
Why Sankalp spent three years writing code with zero revenue before getting his first customer in 2021
How a $2 warehouse pick turns into a $15 pick because of one inventory location error, and how Gather cut that by 70% for Barrett
The land and expand math: customers start with 5 facilities and expand to 100 within three years at $500K per facility network
Why 170% net revenue retention is possible when your product is embedded in daily warehouse operations
How Gather AI built neural nets that can read barcodes a standard grocery store scanner cannot, with no human annotation required
Why Sankalp passed on big-name VCs and chose Smith Point Capital, founded by Keith Block, former CEO of Salesforce
The forklift vision product that turns any warehouse into an Amazon Go store using off-the-shelf hardware from Best Buy
How Sankalp was carrying suicidal thoughts since his teenage years and only discovered life without them a year and a half ago, while building a company past $9M in revenue
The Series B math: $40M raised at roughly $270M to $400M valuation selling 10 to 15% of the business at $15M in revenue
Why Gather AI is touching just 0.1% of its addressable market today, and what 1% would actually mean in dollar terms
Connect:
YouTube: Nathan Latka
Gather.ai: gather.ai
Founderpath: founderpath.com