Provides a data flow security platform that monitors, classifies, and remediates sensitive data transfers to third-party APIs and AI tools. It automates redaction, redirection, and compliance workflows, ensuring data residency, privacy governance, and protection against accidental leaks. Deployed on-premises or in private clouds, it enables organizations to maintain control and visibility over their data in transit.
Funding
$8.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations lack comprehensive visibility and control over sensitive data transmitted to third-party APIs and AI tools, increasing the risk of data leaks, compliance violations, and security breaches. Existing solutions often fail to provide real-time monitoring and automated remediation of risky data flows.
Solution
Riscosity provides a data flow security platform that enables organizations to discover, analyze, and remediate sensitive data in transit to third parties and AI services. The platform offers real-time visibility into data flows, identifies sensitive data types, and automates data governance and compliance workflows. By automatically redacting or redirecting sensitive information, Riscosity helps prevent data leaks, enforce data residency policies, and ensure privacy-first AI adoption. The platform can be deployed on-premises or in private clouds, providing organizations with full control over their data.
Target Audience
Riscosity targets security, privacy, and compliance teams within enterprises that need to govern and secure sensitive data flows to third-party APIs and AI tools.
Features
- Real-time data flow monitoring and visualization to identify all third-party API interactions
- Automated sensitive data discovery and classification using pre-built and custom data type definitions
- Data loss prevention (DLP) capabilities with automated redaction, masking, and tokenization of sensitive data
- Data residency enforcement to ensure data is processed and stored in compliance with regulatory requirements
- API cataloging and governance to manage and control access to third-party services
- Integration with Model Context Protocol (MCP) for discovery of data in motion within AI workflows
- Browser extension to prevent accidental data leaks to AI chatbots
- Automated privacy impact assessments (PIAs)