Stacks Raises $23 Million to Reinvent Finance Operations With Agentic AI

WHY THIS MATTERS:
Enterprise finance is becoming the next major function to undergo AI-led transformation. While customer support and legal have already seen significant automation, the Office of the CFO remains heavily dependent on manual processes, fragmented data, and legacy systems. Stacks’ rapid traction — onboarding 30+ enterprise customers and reportedly saving over 100,000 hours annually — highlights both the scale of inefficiency in finance operations and the appetite for AI-native solutions.

By building a unified financial data layer before deploying automation agents, Stacks is tackling a core structural issue: disconnected systems across ERPs, spreadsheets, and data lakes. If successful, this model could shift finance teams from reconciliation-heavy workflows to real-time reporting and strategic analysis — a meaningful evolution in how enterprises operate their finance function.

Stacks, the agentic platform for enterprise finance, has raised a $23M Series A led by Lightspeed, with EQT Ventures, General Catalyst, and S16VC doubling down. The round comes less than a year after Stacks’ $12 million seed financing led by General Catalyst, underscoring the company’s rapid traction and momentum.

Finance is emerging as the next major enterprise function to be rebuilt with AI. After the multibillion-dollar transformation of businesses’ customer support and legal functions, the shift is now moving into finance, one of the most labour-intensive cost centres for large companies.

Since emerging from stealth less than a year ago, Stacks has onboarded more than 30 enterprise customers globally, saving finance teams over 100,000 hours annually by automating reconciliations, journal entries, and the month-end close.

Founded in Amsterdam and headquartered in London, Stacks counts among its global customer base a number of leading European scaleup businesses including Volt, Motorway, Cleo and Bloom & Wild.

Building the Financial Data Layer for AI

Fragmented data remains one of the biggest structural barriers in enterprise finance. Transaction-level detail is scattered across ERPs, spreadsheets, data lakes, and legacy systems, forcing teams into manual workarounds because core platforms are slow, difficult to integrate, and not built for AI.

As a result, finance teams spend more time reconciling numbers than operating with real-time visibility.

Stacks built its platform by solving this foundation first. The company developed a data layer that connects directly to finance systems and creates a single, consistent financial view across them. It has also built deterministic machine-learning tooling required to make automation reliable at enterprise scale. On top of that foundation, Stacks has deployed agents that automate operational workflows across the finance stack, delivering materially better speed, accuracy, and leverage to finance teams.

“Stacks is uniquely positioned to tackle some of the toughest challenges in enterprise finance,” said Alex Schmitt, Partner at Lightspeed. “The team’s mix of technical and finance expertise from Uber and Plaid, along with the company’s remarkable traction, gives us strong conviction that they will lead the AI shift inside the Office of the CFO.”

Finance Teams Report Immediate ROI

Stacks is already delivering strong results in its first core module, Month-End Close, and seeing growing adoption in day-to-day operational workflows.

“The time savings are material. We were surprised just how quickly the value showed up,” said Jack Nottage, Head of Finance at Motorway, the online used car marketplace, whose finance team reconciles several thousands of payments weekly and was able to cut time spent handling reconciliation by 40 hours per month within weeks of integrating with Stacks. 

“With Stacks, we’re saving a noticeable amount of time on the finance close, and as a result we can produce the management accounts faster each month,” said Andy Murray, Head of Finance at Cleo, the AI-native personal finance assistant, who onboarded with Stacks to improve the team’s critical workflows. Cleo now enjoys 80% faster journal entry processing and the ability to pull data between systems to produce enhanced financial reports within seconds.

“We slashed our monthly close time by eight days,” said JP, Global Head of Accounting at global jewelry trading platform, Nivoda. “Journal postings went from days to minutes, and we automated 95% of reconciliations.”

Stacks Expands Beyond Close Automation Into Reporting

With its data foundation in place, Stacks is expanding into financial intelligence.

The company today introduced a new reporting and analysis suite aimed at moving finance teams beyond manual reporting and toward automated business explanation.

At the center of the launch is AI Flux Analysis, a product that automates variance analysis and replaces spreadsheet-based commentary with explainable, account-level investigation. Flux identifies variance drivers across transactions, pulls historical context across periods, and generates explanations that finance teams can review and refine. The first clients using Flux have reported a faster journey – from days to minutes – to report completion and greater certainty in findings. 

Stacks is also introducing a leadership-ready executive summary, which represents the first layer of a broader intelligence suite for enterprise finance.

From Close Automation to End-to-End Agentic Finance

Stacks is targeting both the $100 billion Office of the CFO software market and the far larger labor spend still powering enterprise finance with an AI-native platform built from the ground up. The close and reconciliation space remains dominated by incumbents like BlackLine, HighRadius, and OneStream, whose aging systems are costly to deploy and poorly rated by customers.

“We started with the most manual and foundational workflows in finance: accounting and the close,” said Albert Malikov, Founder and CEO of Stacks. “From day one, we focused on solving the core problem: fragmented data. By building an AI-ready data layer, we’re unlocking what’s needed to bring AI agents into operational finance, shifting CFO teams from process execution to higher-value analysis and decision-making.”

FF NEWS TAKE:
Stacks isn’t just automating the month-end close — it’s positioning itself as infrastructure for “agentic finance.” That’s a bold play in a market long dominated by incumbents with complex, hard-to-integrate systems.

The real differentiator will be execution at scale. If Stacks can prove that AI-driven reconciliation, journal automation, and variance analysis consistently deliver measurable ROI in large enterprises, it could carve out meaningful share in the $100bn CFO software market. Finance may not be flashy, but it’s mission-critical — and that’s exactly where durable AI platforms are built.