kitio.aiAdded Oct 29, 2026
PVML
PaidSecure virtual databases for running AI on existing data
What is PVML?
PVML lets IT teams create secure virtual databases on top of existing infrastructure so generative AI can use company data without copying it. It is aimed at CIOs and enterprise IT dealing with AI data access risks.
The company argues that autonomous agents inherit user permissions without context-aware controls, which raises the chance of data leakage. Its virtual databases add built-in security and governance so each AI use sees only what it should.
No rows of data are moved or duplicated. The homepage mentions a partnership with VisionWave for secure autonomous AI in defense operations, and access starts with a booked demo.
Features
- Unlimited virtual databases
- No data movement or duplication
- Built-in security controls
- Governance for AI agents
- Runs on existing infrastructure
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Releases
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Organization
PVML
Listed by kitio.ai · unverified owner
Pricing
- Pricing model
- Paid
- Paid options from
- Not listed
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Pros and cons
Pros
- Leaves data where it already lives
- Targets AI agent permission risks
- Works with existing infrastructure
Cons
- Demo required, no public pricing
- Aimed at enterprise IT teams
- Few product details on the homepage
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Q&A
What is PVML?
PVML lets IT teams create secure virtual databases on top of existing infrastructure so generative AI can use company data without copying it. It is aimed at CIOs and enterprise IT dealing with AI data access risks.
Does PVML copy my data?
No. The product is built to create virtual databases without moving or duplicating any rows of data.
How do I try PVML?
The site directs visitors to book a demo.
How much does PVML cost?
PVML is paid.
Is there a free version of PVML?
No. PVML is a paid tool.
What are the main features of PVML?
Unlimited virtual databases, No data movement or duplication, Built-in security controls, Governance for AI agents, Runs on existing infrastructure.
Who makes PVML?
PVML is made by PVML.
What are the best alternatives to PVML?
Popular alternatives include Diwo, Snowflake, Databricks.