Galdera Raises €1.5m to Redefine Financial Planning with AI-Powered Reasoning

Galdera Labs has successfully closed a €1.5 million pre-seed funding round to transform how companies handle financial planning. The investment was led by J12 Ventures with participation from Antler and strategic angels from companies like Klarna, Stripe, and DeepL. This capital injection will support the development of a platform that moves beyond traditional reporting toward a more sophisticated reasoning infrastructure.

Founded by a trio of former Klarna operators, the team experienced the limitations of manual Excel models during periods of extreme hyper-growth. Evan Rumpza, Mattia Scolari, and Giovanni Casula previously built internal systems that allowed a small team to manage complex forecasting across dozens of markets. They are now bringing those lessons to the wider market to solve the problem of disposable and fragmented financial models.

The Galdera platform is built on a two-layer architecture that combines a high-volume calculation engine with a unique semantic memory layer. This setup allows the AI to understand the strategic intent and executive assumptions behind the numbers rather than just processing raw data. Users can interact with their financial models through natural language querying, enabling CFOs to ask complex questions in plain English.

Unlike traditional tools that require weeks to update, Galdera offers always-on forecasting and rapid scenario analysis. The system ensures that every assumption remains traceable and auditable, creating a reliable institutional memory for the organization. This approach allows finance leaders to simulate pricing changes or headcount shifts instantly, providing immediate clarity on revenue and margin impacts.

Decoded Take

The entry of Galdera into the FP&A market signals a shift from AI as a feature to AI as a foundation in financial software. While legacy EPM tools focus on data aggregation, this new wave of reasoning infrastructure treats the financial model as a living graph of logic and context. For an industry long tethered to static spreadsheets, the ability to maintain auditability while using large language models to interrogate data represents a significant leap in strategic agility.