geniosAI raises $19.1M for AI financial analysis, led by FactSet

The company builds products for corporate finance teams, portfolio managers, analysts and investment bankers. Its platform lets users trace a number in a financial model back to the document it came from, inspect each calculation step and see which assumptions produced the result. The decisions teams make during review are stored alongside the analysis, so when a model is updated, the team can reuse the assumptions and methods from earlier work.

AI agents update the models

The platform splits research, modeling and checking tasks among different AI agents. In an investment banking example shared by the company, one agent reviews a company's newly announced financial guidance, another updates the model by changing the relevant assumptions, and a third compares the updated model with the previous version. The finance team can then follow, step by step, which data the changed figures rely on and how they were calculated.

According to geniosAI, the platform is already used by finance and investment teams at some Fortune 500 banks and technology companies to prepare for earnings announcements. Teams can compare results against competitors' performance and analyst expectations, examine notable differences and prepare for questions analysts may ask.

The traceability angle is what sets the pitch apart: in finance, an AI-generated figure is only useful if a team can verify where it came from. With FactSet data now built in, geniosAI is betting that auditable, reusable analysis will win over teams that have been cautious about AI in modeling work.