Dreamdata built the finance team they think is coming. It runs on Light.

Peter has a simple test for whether a finance stack actually works: can it build a deferred revenue schedule from the commercial data? Dreamdata's couldn't. Commercial reporting and financial reporting lived in different worlds. HubSpot could show the ARR, but finance still had to reconstruct the underlying transaction. And for a team that wanted agents to do more of the work, disconnected systems weren't just inefficient. They were a dead end.

All three entities went live on 1 April 2026. Entities, departments and cost centres now live as dimensions on the transaction itself, instead of being buried inside account codes. But Dreamdata wasn't waiting for the migration to finish before it started building.

That line gets to the heart of how Dreamdata thinks about finance. The aim isn't to put AI on top of the same old processes, it's to decide which work needs a person, then build agents for the rest. Light gives them the financial infrastructure underneath it. Dreamdata supplies the logic that's specific to Dreamdata.

Dreamdata initially built many of its agents adjacent to Light, using Light's API and data as the foundation. The next step is bringing more of that work into the platform itself.

Peter made the case to our product team in July. Light has to build for thousands of companies, Dreamdata only has to build for Dreamdata. That means its team can spend more compute, more context and more tokens solving a very specific finance task, because the alternative isn't cheaper software, it's another hire.

It's also the direction we were already taking Light. Custom Agents landed in Dreamdata's account in August, giving the team a way to bring more of the workflows it prototyped outside Light directly into the platform, while keeping Dreamdata-specific business logic where it belongs.

The App Store follows the same pattern. Dreamdata needed a Zenegy payroll integration, so it built one itself, which proved the use case. Light then built the production Zenegy app for the App Store. It's live today and installs directly in Light, so Dreamdata no longer needs to maintain its own version. Dreamdata builds the thing it needs, Light learns from it, and the best ideas can become infrastructure for everyone.

Dreamdata's Copenhagen office is ten minutes from ours, and that proximity has turned into a pretty direct product loop. Kyle and the product team have run workshops with Peter and Andreas in their office, and Andreas has spent hours stack-ranking card feedback with the team. Features have gone from conversation to product in weeks.

The cash balances endpoint exists because Peter asked for it. The AR aging view came out of the same sessions, replacing analysis Dreamdata used to assemble manually.

The relationship goes both ways. Dreamdata builds things on Light that we learn from, and our product team uses those workflows as input for how Light's own AI layer should work. They're not waiting for us to tell them what AI in finance looks like. They're building their version of it, and pushing us to build faster too.

For most of Dreamdata, finance doesn't happen in a finance system. It happens in Slack. Managers approve bills there, often within minutes. Light pulls receipts from the inbox, and if one is missing, the cardholder gets asked for exactly what finance needs, in the place they're already working. Agents post their results there too.

And finance data is no longer just for finance. Customer success can check whether a customer has paid without asking finance or opening another system. It's what becomes possible when the whole company works from one modern agentic platform.