The AI Workflow Behind Predictable Revenue Growth
Discover FlyCode's AI-native retry workflow that recovers failed payments, reduces involuntary churn, and lifts ARR 5–8%—practical tactics for SaaS & subscription businesses.
🎤 Full Interview: Tzachi Davidovich, Co-founder & CEO @ FlyCode
"Failed payments aren’t just a billing glitch—they silently eat away your best customers’ lifetime value. We built FlyCode so businesses can stop leaking revenue without even knowing it."
Founder Story & Vision
Who they are & what they’re building
Tzachi Davidovich is the Co-founder & CEO of FlyCode, a YC-backed fintech startup from Tel Aviv. With over a decade in fintech and subscription billing—and prior product leadership roles at Pioneer and Behaf—Tzachi set out to tackle a problem that quietly drains billions from SaaS and subscription businesses: failed payments. FlyCode’s AI-native platform predicts when and how to retry transactions, turning invisible churn into predictable recovered revenue.
Why now & what’s the big bet
The subscription economy is booming, but failed payments cost companies $443 billion annually. Most founders accept this as an unavoidable cost, relying on Stripe’s default retries or sending friction-heavy “update your card” emails. Tzachi’s big bet: failed payments aren’t a billing nuisance—they’re a growth lever. With AI, companies can plug this silent leak and boost ARR by 5–8%, without customers even noticing.
🧩 Real-World Use Cases
How it works in the wild
Stripe + SaaS Integration: A B2B SaaS integrates FlyCode directly from the Stripe marketplace. When payments fail, FlyCode’s AI models determine the optimal retry window—recovering revenue automatically overnight.
Shopify Subscription Stores: E-commerce brands with recurring billing layer FlyCode into their stack. Instead of losing subscribers after a random decline, payments are retried at the right time, reducing involuntary churn.
Custom API Deployments: Larger companies with internal billing ops connect FlyCode via API, giving finance teams visibility into recovery rates and eliminating manual spreadsheet chases.
Outcomes: Higher recovery rates, reduced involuntary churn, and ARR uplift—all without customer friction.
What you’ll learn:
How Tzachi identified the “hair-on-fire” problem of failed payments by interviewing 100+ finance teams.
Framework for building predictive retry models that outperform generic billing settings.
Real tactics behind landing early customers through free payment audits.
Lessons from YC on solving urgent problems and keeping teams lean.
How FlyCode turns payment recovery into a strategic growth driver.
Some Takeaways:
Hair-on-fire problems are where startups win. Tzachi only doubled down once finance leaders admitted failed payments were keeping them up at night.
AI isn’t just automation—it’s orchestration. FlyCode’s edge comes from predicting the right time to retry, not spamming retries.
Lean + AI-native beats big teams. With fewer than 10 people, FlyCode builds faster and more effectively than competitors.
CFOs are the real champions. Once they see a 5–8% ARR boost from invisible recovery, adoption becomes a no-brainer.
Don’t start with features, start with fire. FlyCode didn’t even build a dashboard early on—just manual reports that proved value.
In this episode, we cover:
00:01 – The $443B failed payment problem in the subscription economy
00:32 – Why failed payments hit your best customers hardest
02:08 – How FlyCode predicts the right retry timing
03:12 – Stripe marketplace integration and API workflows
05:49 – Understanding involuntary churn and lost LTV
07:59 – Discovering the problem by talking to 100+ finance teams
09:55 – Early customer acquisition through free payment audits
11:09 – Mapping hard vs. soft declines and designing the model
13:16 – Why CFOs love the ARR boost from recovered payments
16:11 – Why Stripe/Shopify don’t solve this deeply
22:22 – Lessons from YC: solving hair-on-fire problems
27:25 – Running lean with <10 people, powered by AI-native workflows
31:59 – Where AI stops and humans are still critical
34:39 – Scaling growth through customers, not fundraising
38:30 – Why empathy + business context remain irreplaceable in AI
41:21 – The importance of saying no as a founder
For inquiries about sponsoring the podcast, email david@thehomabase.ai
Referenced in the Episode:
Stripe Marketplace – FlyCode integration for SaaS billing
Shopify Subscriptions – Recovery for e-commerce recurring billing
Y Combinator – Tzachi’s experience and mindset shifts
Cursor & Claude Code – Tools FlyCode uses internally for AI development
Find Case Studies of all other episodes here.
