The SaaS Podcast: How B2B SaaS & AI Founders Get Customers

ChatGPT turned his product into a commodity at close to $1M ARR. Alon Talmor rebuilt Ask-AI into Mosaic AI, an AI platform for technical support, by narrowing into a market rivals called too hard and selling measurable cost reduction instead of features. The company is now at multiple seven figures in ARR, approaching eight.

Alon breaks down how six months of listening to enterprises produced the product idea, how he closed a $6.5M seed after his co-founder quit in the middle of the round, and how 5-day pilots built on technical support automation turn skeptical enterprise buyers into six-figure customers.

Plus: why he believes the next phase of enterprise AI is agents orchestrating people, not people orchestrating agents.

Alon sold his first startup, BlueTail, to Salesforce, went back for a PhD in AI and question answering, and founded Ask-AI in 2021, a full year before ChatGPT. Today Mosaic AI serves about 100 enterprise customers, with go-to-market in Toronto and R&D in Tel Aviv.

🔑 Key Lessons

Find a blue pond, not a blue ocean: When funded giants crowd your market, narrow into a segment they cannot serve well. Mosaic left enterprise assistants to own technical support and grew past seven figures.

Talk to customers six months before investors: Alon pitched no VCs until enterprises had told him their problem. Yotpo's knowledge chaos became the product, and the seed closed on that proof.

Tell investors bad news before they find it: His co-founder quit mid-raise; he disclosed it immediately and still closed $6.5M. Prettifying reality reads as mistrust, and investors sense it every time.

Sell the cost reduction, not the feature list: Support is a cost center with a known price tag. Mosaic pitches 50-70% savings on a seven-figure budget instead of arguing about features.

Pick the metric your buyer cannot argue with: Tickets per engineer per day survived scrutiny where time-to-resolution failed. One customer measured an 80% lift in a week of the pilot.

Treat build vs buy as your real competitor: With AI coding cheap, enterprises default to building. Win by showing the end state their side project becomes obsolete against, not a feature comparison.

Chapters

What Mosaic AI does and who it's for

The real cost of technical support

BlueTail, Salesforce and the PhD detour

Founding Ask-AI a year before ChatGPT

Losing a co-founder in the middle of the seed round

Radical honesty with investors

Six months of listening before pitching VCs

Yotpo and the design partner playbook

Founder-led sales to the first 25 customers

ChatGPT turns the product into a commodity

Agents orchestrating people

Finding the blue pond: technical support

Build vs buy: the number one competitor

The 5-day pilot and the metric that closes deals

Lightning round

Resources

Full show notes: https://saasclub.io/498

Join 5,000+ SaaS founders: https://saasclub.io/email

He walked into his first pricing call asking for $100,000 and walked out with $10,000 a year. Shahar Azulay had never sold anything before co-founding groundcover, and the product he was selling had no user interface yet, just a sensor and some dashboards. He took it anyway, and still argues that was the right call.

Shahar explains why founders should close their first dozen customers at almost any price, how he published a per-host list price and then discounted it up to 70 percent, and how his first 50 to 100 customers came from his own network plus 10 to 15 LinkedIn messages a day.

Plus: the moment customers started ripping Datadog out on their own, before groundcover had built anything to help them do it.

Shahar Azulay is the co-founder and CEO of groundcover, an eBPF observability platform that lets engineering teams monitor production without changing their code. He has grown it to eight-figure ARR with more than 250 customers, competing head-on with Datadog and New Relic.

🔑 Key Lessons

Close your first dozen deals at any price: Early contract value teaches you nothing. The reps, the reference logos, and learning to survive security and legal reviews are what make the next twenty deals closeable.

Publish your price when you sell to mid-market: A public number per host anchors the conversation and skips a negotiation a first-time founder will lose. groundcover listed $30 per host, then discounted up to 70 percent.

Don't expect to grow your earliest accounts: Shahar never planned to 10x those first contracts. Chasing them traps you in old relationships when the rest of the market is still unsold and will pay more.

Your first sales calls are really feedback calls: Prospects treat a founder as someone to advise, not buy from. Shahar framed early meetings as "we'd love to show you what we're building" and converted from there.

Selling the deal is not replacing the incumbent: groundcover closed customers who still kept Datadog running. The post-sale migration motion only got built after those early displacement attempts visibly failed.

A remote first hire with no local team will fail: The first SDR in North America was hired alone, remote, under marketing, with no one around him. Shahar calls it a failure of gravity, not of the person.

Bet on the technology your team can already build: eBPF worked for groundcover because the founders came from cybersecurity and knew how to ship a safe kernel agent. Incumbents selling SDKs still struggle to copy it.

Chapters

Introduction

What groundcover does and who buys it

Why observability pricing stopped making sense

Bring your own cloud and charging per host

From Apple and cybersecurity to founding groundcover

Discovering eBPF and betting the company on it

Why no other observability vendor was using eBPF

The first customer, three months in

Asking $100K and closing at $10K

Why founders should close at any price

Publishing list pricing and discounting 70%

Being the entire sales function

Prospecting on LinkedIn, 10 to 15 a day

Getting out of the friend zone on sales calls

Hiring the first AEs, SDRs and sales engineers

When customers decided it could replace Datadog

Failing to rip out the incumbent

Learning when you have no leverage

Lightning round

Resources

Full show notes: https://saasclub.io/497

Join 5,000+ SaaS founders: https://saasclub.io/email

He closed most of the deals himself. It took him ten years to stop. Ross Andrew Paquette bootstrapped Maropost to around $50 million in ARR, and for most of that run he was the discovery call, the demo and the follow-up. It worked well enough to take the business from $300,000 to $27 million in 28 months with six or seven people. Then the thing that built the company became the thing capping it.

Ross breaks down how he won accounts paying $10,000 a month on a five-minute response time rather than features, how two people signed brands like Rolling Stone and Mercedes off a conference floor, and why seven or eight experienced sales leaders all failed at Maropost before he changed what he hired for.

Plus: why he took investor money he did not need, and what it felt like to write a $37 million check three years later to buy it back.

Ross Andrew Paquette is the founder and CEO of Maropost, a commerce and marketing platform with roughly 300 people and 5,000 customers. He started it in 2011 out of his apartment while still selling Oracle ERP software full time, planning on ten customers and a quieter life.

🔑 Key Lessons

🤝 Win on service before you can win on product: Ross offered 24-hour live chat and a five-minute reply when Maropost had ten or fifteen customers, and landed accounts paying $10,000 a month without the deepest feature set.

🎯 Sell to people who already trust you: Three or four customers from Ross's previous jobs signed almost immediately, which is why Maropost had real revenue before it had a finished product or any marketing spend.

⚡ Founder demos beat decks: Ross ran simple discovery then a personalized demo with no slides, and credits his edge to having designed the features himself rather than to any sales methodology.

🚀 Concentrate spend where your buyers already are: Buying top-tier sponsorships at a handful of conferences let two people sign brands like Rolling Stone and Mercedes off the floor, helping take Maropost from $300,000 to $27 million.

🧠 Hire for tenacity, not logos: Seven or eight sales leaders with strong resumes failed at Maropost because their experience came from different engines, price points and company sizes that did not transfer.

💰 Capital you do not need still costs you: The 2016 secondary brought expectations rather than money Maropost required, and growth fell from around 400 percent to 6 to 10 percent before Ross bought the investors out.

📉 Getting out of founder-led sales takes longer than you think: Ross spent about ten years moving from what he called "Ross and Co" to an actual organization, and says it was the hardest part of building the company.

Chapters

What Maropost does and who it serves

The ten-customer lifestyle plan

Getting the first customers from old relationships

The developer who kept disappearing

His mother's advice and the oDesk hire

Charging $10,000 a month with a small product

Why most founders cannot sell

From $300K to $27M in 28 months

Why seven or eight sales leaders failed

Writing the $37 million check

Resources

Full show notes: https://saasclub.io/496

Join 5,000+ SaaS founders: https://saasclub.io/email

He never bought a keyword, never ran content marketing, and the big outbound sales force he tried did not work. Rodney Robinson still grew TabaPay to $100 million in revenue, almost entirely through inbound, on a single $2.5 million seed round that stayed the company's only outside money for nine years.

Rodney explains how he found a problem Mastercard could not solve, why he chased small fintechs instead of big logos, how his inbound marketing came from banks and the card networks rather than ads, and why he believes outbound sales no longer works in B2B.

Plus: the six-month lawsuit that cost TabaPay its sponsor bank, and what Rodney had personally put on the line to get that bank in the first place.

TabaPay is payment processing infrastructure that gives fintechs one API to move money instantly in both directions, and processes payments for companies like Dave. The company runs at $100 million in revenue with about 150 people, profitable, growing 35 to 40 percent a year. On the day this interview was recorded, Rodney announced a $155 million raise and the acquisition of a bank.

🔑 Key Lessons

Build what the incumbent is forbidden to build: Mastercard would not add pull payments because it would compete with its biggest processors. That structural refusal, not a missed feature, was the opening TabaPay walked through.

Make the trusted party your sales channel: Fintechs do not know a new processor, but they trust their bank and Visa. TabaPay processes for about 20 banks and lets those relationships generate its inbound pipeline.

Solve revenue before expense: Rodney paid vendors above market to reach the market in a year, charged what it would bear, then displaced the vendors later. Getting to revenue outranked protecting early margin.

Chase minnows, not whales: The first ten customers were small fintechs where the founders already knew each other. Those minnows grew into whales, and the relationship carried through the growth.

Reliability is the product for infrastructure: Three vendors at 99 percent availability leaves you down about 3 percent of the time. Customers bet their business on payments working, so TabaPay took the stack in house.

Expect arrows in year one: Six months in, another company claimed TabaPay stole its software and the sponsor bank dropped them. They won, but only because there was nothing to find.

Chapters

What TabaPay does

$100M in revenue with 150 people

The $2.5M round that lasted nine years

Raising $155M and buying a bank

The problem Mastercard would not solve

Finding the wedge by listening

How the money actually moves

A year to build the first version

Solving revenue before expense

Pledging his house for a sponsor bank

Landing the first ten customers

Chasing minnows instead of whales

When vendors go down

Owning the stack end to end

Channels that wasted time

Why outbound sales is dead in B2B

Building the inbound engine

Pricing against commoditization

Fraud data as a value-add

The lawsuit that cost them their bank

Making every customer feel like the biggest

Why buy a bank

Lightning round

Resources

Full show notes: https://saasclub.io/495

Join 5,000+ SaaS founders: https://saasclub.io/email

He needed a big retailer's data to build the product. No big retailer gives data to a company with no product. Felix Hoffmann solved it sideways: 7Learnings sold a paid consulting project, kept the right to use the data, and built its predictive pricing product on top of it. Ten customers later it was at $1M ARR, and he had closed every one himself.
Felix explains why a demand forecasting product cannot start with a small customer, how he structured the first pilot as an A/B test so a retailer could hand over half its prices without betting the business, and what happened when the first run came back far too expensive.
Plus: how a pricing optimization company prices itself, and why he refuses success-based fees even though he can prove the uplift.
7Learnings is a Berlin company whose software forecasts demand for each product at each price, then sets the price that hits a retailer's goal. It is now at multiple seven figures in ARR with around 40 customers. Felix spent six years as a pricing consultant at Kearney and two years running price optimization at Zalando before founding it.
This episode is brought to you by:
🤖 Hobbes → Don't book a demo. Take one.
🔑 Key Lessons
🎯 Solve the data cold start by selling something else first: 7Learnings could not train a forecasting model without a large retailer's sales history, so it sold a paid consulting project and kept the right to use that dataset.
🤝 Shrink a scary ask into a reversible test: Retailers would not hand pricing to an algorithm outright, so 7Learnings ran an A/B test on half the assortment while the retailer's own team priced the rest.
📉 Pick an early customer who can survive a failure: The first live pricing run was badly wrong on high-priced products. It survived because the buyer had a big enough problem, no alternative, and understood they were working with a startup.
💰 Price high enough to lose some deals: His test is blunt. If nobody is walking away because you are too expensive, you are too cheap, especially for a complex product carrying real delivery cost.
🚀 Founder-led sales lasts longer than founders expect: Felix closed all ten customers behind the first $1M ARR himself, and stayed closely involved through the next forty, because handing off enterprise sales is genuinely hard.
⚡ Pick the technology after the problem, not before: Felix argues founders are all digging in the same technical space, and that decisions needing determinism, low cost and explainability should not be handed to an LLM.
Chapters
Where the idea came from: Kearney, then Zalando
The hardest part was finding co-founders
The consulting project that funded the product
Finding the first paying customer
Structuring the first deal as an A/B test
The first upload was a disaster
How a pricing company prices itself
Ten customers to $1M ARR
The price matching objection
Why LLMs don't belong in the pricing decision
Resources
Full show notes: https://saasclub.io/494
Join 5,000+ SaaS founders: https://saasclub.io/email