Stacks, an agentic AI platform built for enterprise finance teams, has raised a $23 million Series A as it looks to modernise one of the most manual and expensive functions inside large organisations.
The round was led by Lightspeed, with existing investors EQT Ventures, General Catalyst, and S16VC doubling down. The funding comes less than a year after the company鈥檚 seed round (which the company says was led by General Catalyst), signalling fast traction in a market that is suddenly attracting serious investor attention.
Stacks is headquartered in London, with roots in Amsterdam, and is positioning itself as part of the next wave of AI-driven enterprise transformation – this time focused on the 鈥淥ffice of the CFO鈥�.
While AI adoption has already reshaped functions like customer support and legal operations, Stacks believes finance is now next in line.
And the timing makes sense: finance teams remain buried under reconciliations, journal entries, spreadsheet reporting, and month-end close processes that still rely heavily on human effort.
30 Enterprise Customers In Under a Year
Since emerging from stealth less than a year ago, Stacks says it has onboarded more than 30 enterprise customers, including names such as Epidemic Sound, Pleo, Cleo, Bloom & Wild, Volt, Motorway and Nivoda.
The company claims its customers have collectively saved more than 100,000 hours annually by automating reconciliation work, journal entries and month-end close tasks – a strong early signal that there is demand for AI tooling that goes beyond surface-level productivity gains.
鈥淪tacks is uniquely positioned to tackle some of the toughest challenges in enterprise finance,鈥� said Alex Schmitt, Partner at Lightspeed, pointing to the team鈥檚 mix of finance and technical experience from companies like Uber and Plaid.
Stacks was founded by Albert Malikov, who previously held product leadership roles at Uber and Plaid.
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Building a Data Layer Before Deploying AI Agents
Unlike many AI-first fintech tools that focus on flashy copilots or dashboard overlays, Stacks is pitching a more foundational approach: build the underlying financial data layer first, then deploy agents on top of it.
The company argues that one of the biggest blockers in enterprise finance is that transaction-level financial data is scattered across ERPs, spreadsheets, data warehouses and legacy platforms. This fragmentation forces finance teams into manual reconciliation and reporting work because core systems are slow, complex to integrate, and not designed for AI.
Stacks says it has built a platform that connects directly to finance systems to create a single, consistent view across them. It has also developed deterministic machine-learning tooling to make automation reliable at enterprise scale – a key requirement for finance teams where 鈥渕ostly correct鈥� is not good enough.
Early Customers Report Measurable ROI
Stacks is already seeing adoption through its first core module, Month-End Close, and says it is expanding into more day-to-day operational finance workflows.
Customer testimonials included in the announcement point to immediate impact.
Motorway鈥檚 Head of Finance, Jack Nottage, said the company was able to cut reconciliation time by 40 hours per month within weeks.
At Cleo, Head of Finance Andy Murray said Stacks delivered 80% faster journal entry processing, while also enabling faster cross-system reporting.
Nivoda, a global jewellery trading platform, reported that it reduced its close cycle by eight days, automated 95% of reconciliations, and cut journal posting time from days to minutes.
Launching AI Flux Analysis To Move Beyond Reporting
Alongside the Series A, Stacks also announced the launch of AI Flux Analysis, positioning it as the company鈥檚 second major cornerstone product.
Flux analysis is traditionally one of the most spreadsheet-heavy, manual reporting processes in finance, requiring teams to explain variances across periods and identify what drove performance changes.
Stacks says its new tool automates variance analysis by identifying variance drivers at a transaction level, pulling historical context, and generating explanations that finance teams can review and refine. Early customers reportedly reduced report completion time from days to minutes.
The company is also introducing a leadership-ready executive summary feature, which it describes as the first layer of a broader financial intelligence suite.
Aiming for the CFO Software Market and Beyond
Stacks is targeting the $100 billion Office of the CFO software market, but it is also aiming at an even bigger opportunity – replacing the labour-intensive processes still powering enterprise finance.
The company is entering a space dominated by incumbents such as BlackLine, HighRadius and OneStream, arguing that legacy platforms are costly to deploy, difficult to integrate, and poorly rated by customers.
鈥淲e started with the most manual and foundational workflows in finance: accounting and the close,鈥� said CEO Albert Malikov. 鈥淏y building an AI-ready data layer, we鈥檙e unlocking what鈥檚 needed to bring AI agents into operational finance, shifting CFO teams from process execution to higher-value analysis and decision-making.鈥�
With fresh capital and an expanding product suite, Stacks is betting that the next major enterprise AI battleground won鈥檛 be engineering or customer support – it will be the finance department.
