Datavillage provides a platform for confidential analytics and trusted AI by enabling secure data collaboration without exposing raw data. The system utilizes trusted execution environments to allow organizations to connect sensitive, siloed data for shared intelligence and risk analysis. This approach facilitates compliance-driven insights for fraud detection and AML while maintaining data privacy and control.
Funding
$1.2M 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 face challenges in leveraging sensitive, siloed data for analytics and AI due to privacy concerns and regulatory compliance requirements. This data fragmentation hinders the ability to detect sophisticated fraud patterns and improve Anti-Money Laundering (AML) processes.
Solution
Datavillage provides a confidential analytics platform that enables organizations to securely access and analyze sensitive data without direct exposure or movement. The platform facilitates private risk signal exchange, allowing multiple parties to collaborate and uncover hidden patterns by sharing insights rather than raw data. Its AI agents are designed to accelerate alert investigations by analyzing combined internal and external signals in a compliant manner, ensuring no personal data is retained. This approach enhances real-time risk intelligence for more precise decision-making during transactions and onboarding processes.
Target Audience
The primary customers are financial institutions and enterprises operating in regulated industries that require advanced analytics for fraud detection and AML compliance while maintaining strict data privacy.
Features
- Secure, privacy-preserving data collaboration environment for sensitive analytics.
- Private risk signal exchange protocol to identify patterns across disparate datasets.
- AI-powered agents for automated alert triage and investigation in fraud and AML contexts.
- Trusted execution environment ensuring data protection and auditability throughout analysis.
- Capability to integrate internal, PSP, and telco signals for comprehensive risk assessment.
- Configurable agent behavior with full audit trails to meet regulatory compliance.
- No direct data movement or exposure required for analysis.