MagicMirror offers an on-device GenAI observability platform that provides real-time visibility into tool usage and identifies impactful workflows. It ensures data privacy and security by executing Small Language Models locally, enabling safe GenAI adoption and employee productivity.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations face significant challenges in safely adopting Generative AI (GenAI), including a lack of visibility into usage, difficulty identifying impactful workflows, and risks associated with data privacy and security. This hinders productivity gains and creates potential compliance issues.
Solution
MagicMirror provides an on-device GenAI observability and enablement platform designed to address these challenges. It offers real-time visibility into how GenAI tools are being utilized across an organization, enabling the identification of high-impact use cases and automation opportunities. The platform also facilitates employee productivity by providing guidance and support for GenAI adoption. Crucially, MagicMirror ensures data privacy and security through local execution of Small Language Models (SLMs) and custom policy generation, preventing sensitive data from leaving the user's device.
Target Audience
The primary target audience includes enterprises and organizations seeking to safely scale their GenAI adoption, improve employee productivity, and maintain data privacy and security. This encompasses IT leaders, CISOs, and department heads responsible for AI strategy and governance.
Features
- On-device Small Language Model (SLM) for real-time data classification and protection without cloud exposure.
- Full local execution within the browser or local environments, eliminating sub-processor risks and ensuring data containment.
- Real-time usage monitoring of GenAI tools, tracking access, user, and session-level actions.
- Shadow AI detection to identify unauthorized tools and hidden AI agents.
- Session-level risk scoring based on authentication, tool configuration, and account type.
- AI ROI tracking with analytics for usage by role or department to inform AI strategy.
- In-browser enforcement capabilities via a browser extension for dynamic policy application.
- Just-in-time user guidance for promoting approved tools, correct configurations, and proper authentication.
- SLM-powered data anonymization and de-anonymization for sensitive information processed locally.
- Extensible API and SDKs for integration into existing applications.
- A policy generator tool to create custom AI policies based on organizational risk tolerance and asset types.
- Support for major LLMs including ChatGPT, Gemini, Claude, Copilot, and custom LLMs.