AI DLP
Your employees use AI every day. Do you know what they're sending?
Patient records. Client names. Social Security numbers. API keys. veild.ai catches sensitive data on the device before it reaches any AI service, whether it left from a browser tab, a desktop app, or a terminal, and puts the real values back in the answer. Your employees keep using AI. Your data never leaves.
Security teams have two AI problems. Most tools solve one.
You cannot inventory every route AI takes out of your organization. And every control strong enough to matter tends to break the work it protects, so people quietly route around it. veild.ai is built for both, and the second one is the part nobody else solves.
Every plane AI travels on
Controls built per tool — a browser extension, a plugin, an approved app list — stop at whatever nobody thought to integrate. veild.ai works one layer down, on the device itself, so coverage doesn’t depend on which interface someone opened this morning. What your developers adopt next quarter is already covered.
- Browser tabs, desktop apps and IDE extensions
- The terminal: CLI tools, scripts and background agents
- Direct API calls, with no supported-app list to maintain
Context survives the protection
An AI model can only reason about what it can see. Take the data away and you haven’t just protected it — you’ve changed what the model is able to do. The same prompt under all three approaches, and what each one actually sends.
Block the request
No answer. The employee opens the same tool on a personal laptop and finishes the task there. You protected one prompt and lost the visibility on everything after it.
Redact the values
MRN [REDACTED], card [REDACTED].
A template with holes in it. The model cannot address, reference, or calculate against a value it cannot see, so the employee finishes the job by hand — often by pasting the real record somewhere you don’t control.
veild.ai substitutes the values
MRN-5528013, card 4916-3355-7201-8846.
A finished draft. The substitutes are structurally valid — a real checksum, a real record format — so the model behaves as if it held the genuine record. The real values are restored on screen; the provider never saw them.
Why this is a security argument, not a convenience one. A control your people work around is worse than no control: you lose the data and the visibility, and you find out from an incident rather than a dashboard. Preserving context is what keeps the protection in the path. Adoption is the enforcement mechanism.
Detect. Mask. Unmask. Audit. Without breaking AI.
veild.ai sits between your employees and AI services. Sensitive data is caught and replaced in flight, so the AI still does its job, your data never leaves the building, and every event is logged.
Detect
Every prompt is scanned for PII, PHI, PCI and credentials before it leaves the endpoint. Hundreds of recognizers, configurable categories, custom patterns per organization.
Mask
Format-preserving fakes replace real values inline, so the AI sees structurally valid data and stays useful. Your originals never reach OpenAI, Anthropic, Microsoft or Google.
Unmask
On the way back, fakes are swapped for the originals so the person sees their real data restored. No copy and paste, no broken workflow.
Audit
Every AI-bound event is logged with what was masked, by whom, to which service, without storing the sensitive value. Built for SOC 2, HIPAA and GDPR evidence.
One platform. Editions for regulated work.
The core platform protects every organization. Industry editions add the data types and the compliance evidence a regulated team is assessed against.
See every tierEnterprise Mid-size organizations with a security team |
Shadow AI discovery, employee risk scoring, and a Coverage Report with SOC 2, PCI-DSS, GDPR and CCPA evidence. SSO, SIEM export, staged rollouts. | $25/user/mo |
Legal Solo attorneys to multi-office firms |
Attorney-client privilege protection. Published case law passes through; active client matters do not. ABA Opinion 512 reports. | $20/user/mo |
Healthcare Health systems, hospitals and practices |
PHI detection across four sensitivity tiers. Clinical vocabulary passes through while patient identifiers are masked. HIPAA evidence. | $35/user/mo |
Financial services Capital markets, wealth management, banking |
Routing numbers, security and counterparty identifiers, and employer tax IDs, each checksum-validated. GLBA and SEC 17a-4 evidence. | $35/user/mo |
Your employees are already using AI. Start protecting the data today.
Three in four knowledge workers use AI at work, and the average breach now costs $4.88M (IBM Security, 2024). Talk to our team about how veild.ai protects your organization.