Genie

Ask data questions in natural language and get instant answers and visualizations, without requiring complex SQL or technical expertise.
Data Visualization Natural Language Query AI-Powered Analytics

Genie is an AI data analyst designed to empower business users to query and visualize their data without the need for complex SQL. By leveraging AI, Genie lets teams ask data questions in natural language and get answers and visualizations in seconds, all while seamlessly integrating with popular workspaces like Slack and Teams.

Some of the key features of Genie include:

  • Powerful & Customizable AI: Anyone can ask data questions and get answers in seconds, connecting to a wide variety of files, databases, or APIs.
  • Locally Running, Privacy Aware, No Internet Required: Runs self-hosted LLMs in your infrastructure, so you can keep your data safe and secure.
  • Made for Institutional Clients: Built to ensure quality and security, so it's perfect for enterprise customers.

Genie is great for organizations because it:

  • Delivers Insights in Seconds: No more waiting for data teams to provide insights, so you can save time and effort.
  • Allows Complex Queries: Chain queries on top of each other, so you can learn from the past.
  • Requires No SQL Skills: Generates SQL for you, so you don't have to manually edit.
  • Integrates All Data: Connects to multiple data sources, so you can keep them up to date on demand.
  • Saves Cost and Time: Reduces compute and downtime costs, so you can run more efficiently.

Pricing models are flexible to accommodate different use cases:

  • Out of the Box Monthly Subscription: Uses a fine-tuned proprietary LLM in a cloud app or integration.
  • White Label Solution: Runs Genie in your infrastructure in an air-gapped solution.
  • Fine-Tuning-as-a-Service: Adapts foundation models to your business and specific data.

Genie is great for institutional clients who want to analyze and visualize data without complex SQL requirements, while keeping data safe and running efficiently.

Published on June 13, 2024

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