Rose AI

Founding Date

Rose AI is a cutting-edge cloud data platform that leverages generative AI to help users find, visualize, and share data. Rose enables seamless integration with the world's top data providers. By combining powerful natural language processing and state-of-the-art open source LLMs, the platform empowers knowledge workers to research at the speed of thought, starting with the finance industry. Rose is a trusted third-party data marketplace where rich datasets can be previewed, bought, and sold with ease. It enables integration of external and internal data, with the ability to permission data for internal teams or third parties.


  • Find data with ease.

    Uses the latest in open-source LLMs and natural language processing to parse and visualize information based on human language prompts.

  • Engage and visualize.

    Built to be fully auditable and allows users to trace the logic of its output all the way back to the raw inputs.

  • Share your insights without friction.

    Frictionless sharing with the ability to permission as much (or as little) data as needed to internal teams or third parties.

  • Buy and sell data.

    A trusted third-party data marketplace where rich datasets can be previewed, bought, and sold with ease.


  • Natural Language Processing (NLPs).

    Users can ask Rose AI questions about their data in plain English, and Rose AI will return answers based on the data.

  • Machine Learning (ML).

    Automate tasks such as data preparation and visualization. This frees up users to focus on more strategic analysis.

  • Cloud Computing.

    A cloud based platform, this makes it easy for users to collaborate on data projects and share their findings with others.


  • Conceptual investment thinking.

    Interpret your questions accurately and understand how to frame and analyze the research to get to a possible answer.

  • Mathematical logic.

    Structure the investigation into your questions, break it into answerable pieces, and add them back up into a world-class answer.

  • Technical engineering to connect to data.

    Connect to your databases as well as build and manage automated processes for working with data.

  • Written and visual synthesis.

    Provide easy-to-interpret answers to your hardest questions using data and clean visualizations.