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Aleph: The AI Platform for Modern Finance

Aleph is building the AI platform for modern finance — one that meets teams where they already work: in spreadsheets. By combining the flexibility of a spreadsheet with the intelligence of AI, Aleph helps companies automate forecasting, reporting, and planning in real time. In this interview with YC Partner Aaron Epstein, co-founders Albert Gozzi and Santiago Perez De Rosso share how they’re rethinking FP&A from first principles, what it’s like building software for some of the world’s fastest-growing companies, and how Aleph scaled to a $29M Series B led by Khosla Ventures, with customers like Zapier, Turo, and Harvey. Chapters: 00:38 – Meeting Finance Teams Where They Are 02:10 – The Pain of Legacy FP&A Tools 04:00 – Building the First AI-Native Finance Platform 06:20 – How Aleph Automates Forecasting & Reporting 08:30 – The Early Days: From YC to First Customers 10:10 – Why Finance Needs to Be Real-Time 12:00 – Designing for Analysts, Not Replacing Them 14:20 – Lessons from Working with Zapier, Harvey & Turo 17:00 – Scaling to a $29M Series B Led by Khosla 19:10 – The Future of FP&A in the Age of AI

Aaron EpsteinhostAlbert GozziguestSantiago Perez De Rossoguest
Oct 23, 202524mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Aleph builds AI-native FP&A around spreadsheets, speed, and trust.

  1. Aleph positions itself as an AI-native FP&A platform that centralizes finance data and lets analysts work directly in spreadsheets via an add-in.
  2. The company differentiates on rapid time-to-value—hours to first value and 1–2 weeks to full implementation—versus months for legacy FP&A deployments.
  3. Early traction came from extensive customer discovery (150–200 calls) that later converted into initial customers, reinforcing a stable product thesis with minimal pivoting.
  4. Because finance is high-stakes, Aleph invested early in trust (e.g., SOC 2 when the team was tiny) and used high-touch customer success to ensure accurate reporting.
  5. With a $29M Series B led by Khosla, the team is focused on pragmatic AI that improves productivity while meeting stringent requirements for correctness, security, and permissions.

IDEAS WORTH REMEMBERING

5 ideas

Meet finance teams where they already work: spreadsheets.

Aleph’s core bet is that adoption improves when FP&A tooling lives inside spreadsheet workflows rather than forcing teams into a wholly new interface or paradigm.

Time-to-value is a primary wedge against legacy FP&A suites.

They claim first value within a day (sometimes hours) and full implementation in 1–2 weeks, countering an industry norm of 3–6 months before meaningful results.

Deep customer discovery can prevent expensive pivots later.

Albert’s 150–200 research calls built strong problem empathy and a durable product thesis; even the pre-seed deck remains largely relevant years later.

In finance software, trust is a product feature, not an afterthought.

They prioritized security early (SOC 2 as a ~3-person team) because customers rely on outputs for CEO-facing reporting and decision-making.

High-stakes domains often require ‘do things that don’t scale’—at first.

Early on, customer success sometimes reviewed numbers with clients pre-send to ensure accuracy; those manual safeguards bought credibility while product capabilities matured.

WORDS WORTH SAVING

5 quotes

Finance people live and breathe spreadsheets, so part of our product is actually within spreadsheets.

— Albert Gozzi

We are… first time to value within a day or less… and then we’re fully implemented in, like, one, two weeks.

— Albert Gozzi

We were SOC 2 certified when we were like three people in the company.

— Albert Gozzi

We won’t let you fail… if for some workflow it needs to be 50/50, we’re gonna do the work for you.

— Albert Gozzi

Most startups die by suicide, not murder… you are your worst enemy.

— Albert Gozzi

AI-native FP&A platform positioningSpreadsheets as the primary workflow surface (add-in)Legacy FP&A pain: long implementations, slow valueCustomer discovery and early customer acquisitionSecurity, SOC 2, and trust with financial dataDoing things that don’t scale (CS “mechanical turk”)Founder evolution and hiring culture (low ego, collaboration)

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