Today we're announcing Stacks' $23 million Series A, led by Lightspeed, with continued support from EQT Ventures, General Catalyst, and S16VC.

I've been thinking about how to write this post for a while. There's the standard version, which includes the milestone, metrics, and market size. We put all of that in the press release. What I actually want to write about is what got us here, and why I'm so energised about what's ahead.

What I'm grateful for

The customers who bet on us early.

When we came out of stealth less than a year ago, we were asking finance teams at large enterprises to trust an unknown company with some of the most sensitive workflows in their business: reconciliations, journal entries, and the month-end close. That's not a small ask. The teams at Epidemic Sound, Nivoda, Datavant, Future PLC, and more than 30 others said yes. They gave us honest feedback, pushed us hard, and stuck with us. Everything we've built that actually works, we built with them. I don't take that lightly.

A team that took the hard path.

We didn't build Stacks by wrapping an LLM around an existing workflow and calling it AI. We started with the unglamorous stuff: the data layer. We connected directly to ERPs, data lakes, spreadsheets, and legacy systems to create a single, consistent financial view, then built deterministic ML tooling to make automation reliable enough for enterprise finance. That foundational work is what makes everything else possible, and it required a team willing to do things that don't scale before building things that do. I'm grateful every day to work alongside people who chose the right way over the easy way.

Our investors, who understood the vision before the metrics proved it.

EQT and Kaushik backed us at pre-seed when Stacks was still a thesis. General Catalyst, Lightspeed, and the others who joined this round didn't just underwrite our traction; they understood what we're building toward. That kind of conviction, from people who've seen a lot of companies, matters more than most founders admit publicly. I'm grateful for it.

What I'm looking forward to

Finance is one of the last major enterprise functions to be fundamentally rebuilt with AI. Customer support has been transformed. Legal is in the middle of it. Finance is next, and it's arguably the biggest opportunity of the three. The labour spent powering enterprise finance dwarfs most people's estimates, and the incumbent software that's supposed to help is expensive, hard to deploy, and increasingly mismatched to what modern teams need.

We started with close and reconciliation because it's the most foundational and the most painful. Automating 95% of reconciliations. Cutting close cycles by eight days. Turning journal postings from days to minutes. These are the kind of outcomes that change what a finance team can actually do with their time.

But close automation was always the starting point, not the destination.

With today's launch of our reporting and analysis suite, including AI Flux Analysis, we're beginning to move finance teams from process execution toward real-time financial intelligence. Automating variance analysis. Replacing spreadsheet-based commentary with explainable, account-level investigation. Giving CFO teams the leverage to focus on decisions rather than reconciling numbers.

That's the shift I'm most excited about: changing what finance teams are actually for inside a company.

We have a long way to go. But for the first time, I feel like the foundation is solid enough to build something truly generational on top of it.

To our customers, our team, and everyone who's believed in this: thank you. Let's get to work.

— Albert