Rose.AI
Rose.AI is a tool. Rose is an AI-powered tool that streamlines the data research process, offering an efficient solution for finding, cleaning, visualizing, a...
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What is Rose.AI?
Rose.AI is a tool. Rose AI is an agentic cloud data platform designed primarily for financial professionals and knowledge workers that simplifies data discovery, visualization, analysis, and sharing.
Rose.AI pricing
Pricing model: Free
Rose AI operates on a freemium model with a Free Tier that provides limited feature set at no cost for getting started. The Pro Tier offers advanced features and capabilities starting from $49.99 per month per user. Higher tiers unlock more volume, advanced integrations, and collaborative options. Larger organizations can request bespoke enterprise quotes. Some datasets may require payment to access, with prices varying by dataset. The entry point is around $0 USD per month on the first paid plan.
Rose.AI pros
- 50+ million time series data points from 30+ vendors ready out of the box
- Natural language AI queries using plain English instead of complex code
- Fully auditable and traceable data points with Logic Trees for transparency
- Autonomous AI agents that self-learn to discover and structure data
- Millisecond real-time data feeds with automated quality assurance
- Unified Data Mesh seamlessly integrates Bloomberg, Refinitiv, and alternative data
- Intuitive interface with short learning curve for new users
- Dynamic visualization tools that transform raw data into compelling narratives
- Seamless collaboration features for sharing workspaces with team contributions
- Data marketplace to preview, buy, and sell datasets in one platform
- Advanced data transformations like :yoy for year-over-year changes
- Rosecode system provides simple keyword-based data search
- Supports both timeseries data and maps (tables) for diverse analysis
- Python library integration for push and pull data operations
- Responsive documentation and email customer support available
Rose.AI cons
- Advanced customization limited on free plans
- Volume capped without upgrading to paid tier
- Niche AI data cases poorly covered
- Not ideal for large enterprises with on-premise needs
- Not a fully open-source tool
- Requires stable internet connection to function
- Ask Rose does not return singular values, only timeseries
- Model is not purely deterministic, may occasionally yield different answers
Frequently asked questions about Rose.AI
What is Ask Rose and how do I use it?
Ask Rose is Rose AI's natural language query system that lets you ask questions in plain English and receive charts in response. It is meant for queries of financial data including equities, macro, FX, and only returns timeseries. To use it, log into your account, go to the Workspace tab, click the Ask Rose button on the left-hand menu to add an Ask Rose module to your notebook, enter your access code, then type your plain-English request and click 'Ask Rose' or press shift+enter to run the query.
What types of data does Rose AI support?
Rose AI supports two types of data: timeseries (a two-column structure with dates in the first column and values in the second) and maps (Rose's word for tables). The platform has 50+ million time series data points from 30+ vendors including equities, macro data, FX rates, GDP, and more.
What is rosecode and how do I use it?
Rosecode is Rose AI's name for a dataset identifier. To use it, type the rosecode into a code module and hit shift+enter or click the play button to run it. For example, typing 'GDP' in a code module will generate a visualization of GDP data. You can also apply transformations using the format rosecode:transformation_name, like 'GDP:yoy' for year-over-year GDP change.
Can I integrate my existing data subscriptions with Rose?
Yes, Rose has thousands of private rosecodes built on data from subscription services like Bloomberg or Market Stack. You can link your existing subscriptions to Rose, though at the moment the linking must be done manually by one of their engineers. Email [email protected] to set up a connection. You can also upload your own data from Excel or Python using the Rose add-in.
How does Rose AI ensure data traceability and transparency?
Rose AI uses Logic Trees to ensure clarity with traceable data points, preserving the integrity of every insight. Every data point, visualization, and answer is fully auditable with a clear trail showing how output logic connects back to raw data inputs. You can click 'Explore all codes' to open results in code modules and see individual timeseries codes and underlying data.
Who is Rose AI built for?
Rose AI is purpose-built for financial analysts and decision-makers, including hedge fund professionals, business analysts, data teams, consultants (like McKinsey), and anyone working with financial data. It was designed by financial professionals from major hedge funds like Bridgewater and Brevan Howard to help knowledge workers research at the speed of thought, starting with the finance industry.
What vendors and data sources does Rose integrate with?
Rose AI has data from 30+ vendors ready out of the box including Bloomberg, Refinitiv, FactSet, and FRED (Federal Reserve's free public API). The platform provides seamless real-time integration across these sources through its Unified Data Mesh, plus alternative data sources and the ability to integrate other public and private datasets.
How do I share data and collaborate with my team in Rose?
Rose AI offers seamless collaboration features that foster innovation by sharing workspaces and allowing team contributions while maintaining data integrity and security. You can control access permissions to keep information secure when sharing with internal teams or external partners. The platform provides a single source of truth that is fully auditable and easy to use for collaboration.
What are the prompting best practices for Ask Rose?
Do: Query Ask Rose explicitly with respect to financial objects (use '10y yield' not just '10y', use 'Vanguard Value ETF (VTV)' not just 'Vanguard Value'), and clarify objects when querying multiple items. Don't: Ask for non-timeseries values (Ask Rose doesn't return singular values), ask for data outside finance (it's trained on finance data), or be surprised if occasionally two different answers appear since the model isn't purely deterministic. Always give feedback using the thumbs up/down button.