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World of Software > News > Agentic finance automation startup Stacks raises $23M in funding – News
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Agentic finance automation startup Stacks raises $23M in funding – News

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Last updated: 2026/02/21 at 4:39 PM
News Room Published 21 February 2026
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Agentic finance automation startup Stacks raises M in funding –  News
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London-based startup Stacks Technologies B.V. says enterprise financial operations are due for a much-needed injection of “agentic” automation after raising $23 million in an early-stage funding today.

Today’s Series A round was led by the high-profile venture capital firm Lightspeed, and saw participation from General Catalyst, EQT Ventures and S16VC. It comes less than a year after the startup closed on a $12 million seed round.

Stacks is the creator of specialized artificial intelligence agents aimed at cleaning up enterprise’s messy financial operations, which are plagued by fragmented data. In many businesses, transaction data is spread across dozens of different systems, including enterprise resource planning tools, spreadsheets, data lakes and accounting tools, making it incredibly difficult to collate and understand. It’s the main reason why financial teams usually end up spending more time on reconciliation than impactful tasks such as analysis and planning.

To help enterprises stay on top of things, Stacks has developed a data layer that connects directly to every financial system used by an organization. This data layer makes it possible to obtain a single and consistent view of the state of a company’s finances. On top of that foundation, it has developed AI agents with deterministic reasoning that can automate operational workflows across the entire financial stack.

Stacks founder and Chief Executive Albert Malikov said the company is taking aim at the two most manual and also foundational workflows in enterprise finance – accounting and month close.

The startup’s agents are designed to automate monthly close operations, account reconciliations, journal entries, variance analysis and reporting, and ensure that everything is synchronized with the organization’s ERP platform. The startup is targeting a legacy “office of the CFO” software market that’s worth more than $100 billion annually. It said enterprises actually spend a lot more than this on their financial operations, though, because the labor costs associated with keeping track of their accounts is far in excess of that number.

“From day one, we focused on solving the core problem of fragmented data,” he explained. “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.”

Following today’s raise, Stacks is now looking to take the next step and move into “financial intelligence” with the launch of its new reporting and analytics suite. The central tool here is called AI Flux Analysis, which uses agents to automate variance analysis, replacing spreadsheet-based commentary with explainable, account-level investigation.

Financial teams can ask simple questions in natural language, and Flux will pull up the answers. For instance, it can identify variance drivers across transactions, pull historical context from across any given time period and provide explanations for any trends or issues teams might identify. The suite also comes with a second tool that generates executive summaries of organization’s financial operations.

To date, Stacks has accumulated more than 30 enterprise customers globally, helping them to save an estimated 100,000 hours of work by automating reconciliations, journal entries and other tasks associated with the month-end close process.

Lightspeed Partner Alex Schmitt said he’s backing Stacks because it has proven it can tackle the hardest challenges in enterprise finance. “The team’s mix of technical and finance expertise, along with the company’s remarkable traction, gives us strong conviction it will lead the AI shift in the office of the CFO,” he said.

Image: News/Meta AI

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