Rose AI

Rose AI is designed around a simple observation: working with data is hard, especially in finance, where analysts juggle fragmented vendors, inconsistent formats, and a constant need to prove where a number came from. The platform addresses this with a unified data mesh that integrates real-time feeds from sources such as Bloomberg, Refinitiv, and alternative datasets, alongside public and private data the user brings in.

At its core is an agentic layer. Autonomous agents discover, clean, and structure data according to a user's requirements, while natural-language querying lets people ask questions in plain English against complex datasets. The system is backed by a financial knowledge bank, so answers are grounded in domain context rather than generic web data.

A distinctive feature is the Logic Tree, which preserves an auditable trail from raw data to final visualization or answer. Combined with real-time processing, automated quality checks, anomaly detection, and collaborative workspaces, this makes Rose AI useful for teams that need both speed and data integrity. Out of the box it offers 50+ million time series from 30+ vendors, ready to use without lengthy data onboarding.