Rose AI

• Natural language querying of data using NLP / LLMs
• Dynamic visual insights & charts from datasets
• Logic tracing: every output links back to raw inputs
• Built-in transformations (100+ data functions)
• Data integration from diverse sources (timeseries, tables, external APIs)
• Collaboration and sharing with scoped permissions
• Data marketplace for buying and selling datasets
• Notebook interface combining narrative, code, and visuals
• Auditability and transparency in data operations
• Versioning/history of transformations and edits

Rose AI is a cloud-based data intelligence platform built for financial analysts, investment professionals, and decision makers who need to derive reliable insight from complex datasets without losing transparency or traceability. The platform is designed so users can pose questions in everyday language—“What was the growth in revenue YoY?” or “Which expense categories spiked?”—and Rose translates that into visualizations, analytics, and narrative outputs.

One of Rose’s standout features is logic tracing: every chart, insight, or computed value retains a visible lineage back to the raw data and transformations applied, ensuring that insight is auditable and credible. Users can upload their own datasets or connect to standard financial/time series sources, after which Rose’s built-in transformations (over 100 kinds) let them compute metrics like growth rates, rolling averages, or ratios with ease.

Rose also offers a notebook environment where text, queries, visualizations, and data modules coexist. Users can combine markdown narratives, code modules, and query modules, then share or publish a notebook.  The platform includes collaborative features and sharing permissions, so teams can jointly explore data while maintaining controlled access.

Beyond its internal use, Rose has a data marketplace where users can preview, license, and trade datasets, giving a way to monetize data assets.  The platform is built by Rose Technology, a company founded by data scientists and investors to modernize financial data infrastructure via low-code and AI interfaces.

Rose supports transformation workflows, version history, and audit logs, which reduces errors and increases trust in insight delivery. It is being adopted in hedge funds, financial institutions, and analytics teams that demand faster insight cycles with traceability.

In short, Rose AI bridges human language and financial data, enabling users to explore, analyze, and share data insights with transparency, while supporting modern data infrastructure and marketplace models.