PVML
Secure real-time data analytics with AI-driven privacy compliance.. [Contact for Pricing]
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What is PVML?
PVML is an integrated platform that connects, accesses, and monitors multiple data sources, providing a collaborative and secure data workspace. It functions as a virtual database for AI, enabling organizations to work directly on live production data without moving, duplicating, or copying data. The platform combines Differential Privacy technology with AI capabilities to ensure real-time privacy and security while allowing users to analyze sensitive data through free text, SQL queries, or external BI tools.
Key features include Differential Privacy and security engine that applies scope and permissions to every query, live data connectivity with zero data movement via high-performance Golang connectors, centralized administration for monitoring all data access from one point, IAM integration with tools like Okta and Active Directory, just-in-time access control, anti-hallucination technology that translates user requests to executable queries, auto-generated AI-ready protocols (MCP, A2A, API), auditability and governance with full logging of every agent action, and the ability to visualize results with auto-generated graphs or customizable charts.
PVML is designed for enterprises, CIOs, IT teams, and CISOs who need to securely operationalize GenAI on existing infrastructure. It serves organizations in fintech, telecom, transportation, healthcare, and insurance industries that need to democratize access to sensitive data for data anonymization, data sharing, and data monetization use cases. The platform is particularly valuable for non-technical users who want to analyze data using free text without writing complex SQL queries.
PVML pricing
Pricing model: Freemium
PVML does not publicly display pricing on their website. The company requires interested organizations to book a personalized demo to discuss pricing and plans. There is no publicly available information about a free tier, paid plan pricing, or what is included in different tiers. The platform appears to be enterprise-focused with custom pricing based on organizational needs.
PVML pros
- No need to move or duplicate data - works with live connections
- Differential Privacy provides true anonymization without PII tagging
- Supports AI free text, SQL queries, and external BI tools
- No installation required - one-step onboarding
- Integrates with existing IAM tools like Okta and Active Directory
- Centralized administration for all data access monitoring
- Real-time privacy and security applied automatically at output level
- Anti-hallucination technology ensures explainable AI queries
- Just-in-time access with time-limited permissions
- Auto-generated AI-ready protocols (MCP, A2A, API) for any AI platform
- Full audit trails for enterprise-grade observability
- Works with any database - data stack agnostic
- Alerting and automated fixes for excessive or conflicting permissions
- Easy collaboration with shared conversations and notebooks
- Auto-generated graphs for quick insights plus customizable visualization
- Production incidents audit with real-time query monitoring
- Invisible to users - doesn't change existing workflows
PVML cons
- Pricing not publicly available - requires booking a demo
- Primarily enterprise-focused may not suit small businesses
- Differential Privacy adds noise that may affect data accuracy
- Requires database connection string details for setup
- Limited information on free tier availability
- May require learning curve for Differential Privacy concepts
- Cloud-based platform may not suit air-gapped environments
- Bias toward AI/ML use cases may limit traditional analytics users
Frequently asked questions about PVML
What is PVML?
PVML is the virtual database for AI - an integrated platform where multiple data sources can be connected, accessed, and monitored, providing a collaborative and secure data workspace. It turns internal data sources into AI-ready virtual databases that are live, scoped, and secure, without moving or duplicating data.
How does Differential Privacy work in PVML?
PVML's Differential Privacy algorithm adds mathematical noise to datasets at the output level, preventing attackers from inferring private information about individuals while still enabling meaningful analysis. It treats all data columns as sensitive, requires no PII tagging or encryption, and provides post-processing immunity against adversaries with auxiliary data.
Do I need to move my data to use PVML?
No, PVML works with live data connectivity and requires zero data movement or duplication. You simply enter your database connection string details, and PVML connects to your existing data sources without moving data outside the organization's environment.
Can non-technical users analyze data with PVML?
Yes, PVML allows non-technical users to analyze data using free text instead of writing complex SQL queries. The platform automatically translates user requests into queries that the data source can process, speeding up time-to-insight while avoiding hallucinations.
What AI platforms does PVML integrate with?
PVML auto-generates AI-ready protocols including MCP (Model Context Protocol), A2A, and API, allowing it to plug into any AI platform such as ChatGPT, Claude, and other AI systems. It connects AI agents to core business data where the real value lies.
How does PVML handle permissions and access control?
PVML provides tailored permissions with full flexibility including JIT (just-in-time) access, Differential Privacy mode, direct access when needed, and complex filtering. The security engine applies scope and permissions to every agent query in real-time, with centralized administration to monitor all access.
What industries use PVML?
PVML is trusted by leading companies from fintech, telecom, transportation, and healthcare industries. Use cases include analyzing data with AI (fintech), anonymization for internal collaboration (insurance), and privacy-preserving data monetization with third parties (telecom).
Is PVML compliant with data privacy regulations?
Yes, PVML undergoes strict external audits to ensure the solution adheres to the highest standards of privacy and security. The European Data Protection Board's Article 29 has affirmed that Differential Privacy is the sole method for achieving true anonymization after reviewing 7 approaches.
How does PVML prevent AI hallucinations?
PVML's anti-hallucination technology automatically translates user requests into queries that the actual data source can process, providing explainability and ensuring results are trustworthy and based on real data rather than AI-generated fabrications.
Can I monitor and audit data access with PVML?
Yes, PVML provides centralized administration with one single point to monitor and control all data access. It offers a high-level admin view over queries, permissions, user requests, and to-dos. Every agent action from query to response is logged for full audit trails and enterprise-grade observability, including production incidents audit with real-time query monitoring.