Daniel Kalish's Speaker Profile
Building the first Agentic AI platform for treasury teams
Meet Daniel Kalish, Co-Founder & CEO of Nilus (Ex-PayPal), helping finance teams move from “yesterday’s numbers” to real-time, auditable action.
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Biography
Who is Daniel Kalish?
Daniel Kalish has spent his career inside the “financial plumbing” that determines whether global companies scale smoothly or stall under complexity. After starting his career at a law firm working on venture capital and M&A, he joined PayPal, where he spent five years driving growth and go-to-market across complex international markets.
That operator’s view exposed a paradox Daniel saw everywhere: even sophisticated companies managing massive cash balances were effectively “liquidity blind,” forced to rely on stale spreadsheets and fragmented bank portals to answer basic questions in real time.
He founded Nilus to eliminate that latency by connecting every system that touches cash (banks, payment processors, ERPs, planning tools) into a single, normalized model that finance teams can actually act on.Â
Today, Daniel leads Nilus as it helps mid-size and enterprise finance organizations replace manual workflows with AI-driven automation: real-time cash position, bottom-up forecasting, reconciliation, and collections enablement, delivering ROI across treasury, accounting, and finance ops.Â
Resources
Highlights
- Co-Founder & CEO of Nilus: AI-powered treasury platform built for high cash complexity environments.
- Scaled Nilus to manage billions in cumulative cash for high-growth companies (including Taboola, Wiz, StackAdapt, Alloy)
- Raised dozens of millions from top-tier investors (including Bessemer Venture Partners and Felicis)
- Former PayPal leader Head of Market Development & GTM for Central & Eastern Europe, Russia, and Israel.
- Academic Background: LL.B + B.B.A, IDC Herzliya (Magna Cum Laude); Zell Entrepreneurship Program.
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Media appearances
Listen to Daniel Kalish's previous interviews
Topics
What your listeners can learn
Topic #1
The End of Static Treasury
Treasury teams have spent decades trapped in Systems of Record, great at storing history, terrible at creating outcomes. But this is exactly what the corporate treasury will look like in the next few years: a shift from reporting to real-time, policy-driven execution.
On your podcast, Daniel will explain the shift to Systems of Action, where AI agents don’t just show idle cash; they propose moves, validate policy constraints, and queue execution for human approval and auditability.
Topic #2
Unlocking Idle Cash Without Adding Risk
Many companies “see” idle cash but can’t move it safely because execution is manual, slow, and error-prone.
On your podcast, Daniel will break down how high-growth teams can unlock yield, reduce debt costs, and operationalize cash optimization by automating workflows (sweeps, reconciliations, variance detection) with approval controls.
Topic #3
From Spreadsheet Forecasts to Forecast Certainty
Most forecasts are fragile guesses built on stale assumptions and spreadsheet drag-and-drop.
On your podcast, Daniel will share how to build defensible forecasts using continuous scenario logic, driver attribution (what changed and why), and evidence-based triangulation across AP/AR/contracts—so finance can defend the number to the Board.
Topic #4
Assurance-Grade AI: Making Autonomy Safe for CFOs
CFOs don’t fear AI – they fear black boxes. Trust requires explainability, reversibility, and auditability.
On your podcast, Daniel will unpack what “Assurance-Grade AI” means in practice: policy reasoning, traceable decision receipts, approval workflows, and governance layers that make agents safer than spreadsheets.
Topic #5
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