geniosAI Raises $19.1M, With FactSet Leading Series A

By Grace Kim

Who backed geniosAI’s $19.1 million round?

geniosAI raised $19.1 million in combined seed and Series A funding and emerged from stealth on November 9, 2026, the financial intelligence startup said. FactSet led the Series A, with Zoom and General Catalyst also investing.

geniosAI said it was bringing products to market for corporate finance and investment teams. The company identifies its San Jose, California, operation as co-founded and led by Chief Executive Officer Prabhdeep Singh. It says its products target the office of the CFO and investment professionals on both the buy side and the sell side.

geniosAI says finance and investment teams at Fortune 500 global banks and technology companies already use the platform for earnings preparation. The listed jobs include peer comparisons, analyst-expectation comparisons, identifying notable items and anticipating questions from analysts.

The takeaway: geniosAI enters the market with $19.1 million, three named backers and claimed adoption among large banks and technology companies.

How does geniosAI make analysis traceable?

geniosAI says its platform is designed to preserve institutional context across investment research and modeling assignments. It displays reasoning and links figures to their sources. The company says that context lets an institution trace a number, challenge the work behind it and build on the same record in a later assignment.

Chief Executive Officer Prabhdeep Singh said: “geniosAI keeps the sources, calculations, assumptions, and review decisions attached to the work, so the institution can trace every number, challenge it, and build on it the next time.”

The practical takeaway: geniosAI is trying to keep the evidence and review history attached to each figure, not merely return an answer.

How do geniosAI’s agents divide the work?

On geniosAI’s website, the company divides its illustrated agent roles into two groups, both of which answer to the user. System 1 is described as quick, certain and narrow, with a Junior Analyst, Controller and Accountant. System 2 is slow, thorough and deep, with a Chief of Staff, Deep Researcher and Senior Reviewer.

• In geniosAI’s office-of-the-CFO example, a Controller opens the ledger, an Accountant reconciles 412 lines, the Controller flags two variances and a Chief of Staff drafts a board summary.
• In an investment-banking workflow, a Deep Researcher reads new guidance, a Junior Analyst changes three drivers and rebuilds the model, and a Senior Reviewer checks it against the previous version.
• In another example, geniosAI follows a requested figure back to its filing, replays the calculation and identifies who produced it.

The examples put source tracing, model revision and responsibility for a calculation into one review chain. They also show the intended order of work: retrieve and verify, change and rebuild, then compare and review.

The practical takeaway: geniosAI is selling a review chain, not just an answer: source, calculation, model change and reviewer all stay linked.

What do the strategic investors say?

FactSet’s role extends beyond the Series A because it is also geniosAI’s strategic partner. FactSet Chief Executive Officer Sanoke Viswanathan said the partnership combines FactSet’s data with geniosAI’s traceable analysis to help teams move from insight to decision.

Zoom Chief Strategy Officer Abhisht Arora said the investment fits Zoom’s focus on moving work from conversation to completion and builds on its work with finance teams and financial institutions.

General Catalyst managing director Madhu Namburi said the larger opportunity is a higher, more consistent level of intelligence across an organization, with judgment remaining with the business.

All three investors describe a practical path: combine data or conversation with analysis, then leave the final judgment with the business.

The next measure for geniosAI is whether source tracing and retained context become embedded in recurring institutional work, making analysis easier to review and reuse across teams.