Accounts payable has produced multiple billion-dollar companies, yet its mirror image, accounts receivable, remains almost entirely manual at most enterprises despite decades of software spend. In this episode, Caitlin Leksana, co-founder and CEO of Fazeshift, explains why AR has remained unsolved and how her company's AI agents are changing that. A mechanical engineer turned BCG consultant turned founder, Caitlin came to the problem the hard way, doing her own AR by hand at a previous startup, and her outsider's view of a stubborn back-office chore is exactly what makes the conversation worth your time.
What We Covered
A million AR analysts doing manual work in the US
Why accounts payable got solved and AR did not
The leverage imbalance between AP and AR departments
The swivel chair problem and fragmented data
$200 million in unapplied cash on one balance sheet
Fazeshift as a context layer, not a rip-and-replace
Why traditional SaaS and if-then logic could never scale AR
The collections, cash application, and AR inbox modules
Human in the loop and building trust when AI touches money
Training agents on historical data and tribal knowledge
From Y Combinator to a Series A led by F-Prime
The vision for the context layer and autonomous finance
Key Takeaways
AR is the inverse of AP, and every bill is someone else's invoice, so the market is at least as large and mostly uncaptured.
The real unlock is not the AI model but unifying fragmented data across the ERP, bank, CRM, and inbox into a single context layer.
Human in the loop with full auditability is what earns risk-averse finance teams' trust, and it is how agents move toward full automation over time.
Some of the best unsolved startup problems are the ones furthest removed from an engineer, because no one with the tools to fix them ever felt the pain.
About Caitlin Leksana
Caitlin Leksana is the co-founder and CEO of Fazeshift, a San Francisco startup building AI agents for accounts receivable. She earned bachelor's and master's degrees in mechanical engineering from Georgia Tech, advised Fortune 500 companies at BCG, and earned her MBA at Harvard Business School before founding a crypto marketing startup and then Fazeshift. The company went through Y Combinator's Summer 2024 batch, raised a $4M seed led by Gradient Ventures, and announced a Series A led by F-Prime in 2026.
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