# Email Drip: AI Data Anonymizer for LLMs
## 5-Email Cold Outreach Sequence

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## Email 1: The Exposure Problem

**Subject:** Your LLM is seeing customer data it shouldn't

Hi [First],

Every prompt you send to Claude, GPT, or Gemini carries risk. Customer records, medical histories, financial data, source code—it all flows through public APIs by design.

Most teams either accept the risk or build expensive data masking layers in-house. There's a third option.

We built Data Anonymizer specifically for this. It strips PII and sensitive patterns before your data ever touches an LLM, leaving the inference intact.

Worth 15 minutes?

[Link]

Regards,
Wes

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## Email 2: The Cost of Homegrown

**Subject:** Why your internal masking layer is a liability

Hi [First],

When I talk to teams running custom anonymization, I hear the same story: it works until it doesn't. A regex misses a pattern. A new data type appears. Compliance asks for audit logs.

Then someone's on-call at 2 AM rebuilding the filter.

Data Anonymizer handles the edge cases. It learns what "sensitive" means in your domain, not ours.

[Link]

Wes

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## Email 3: Compliance as a Lever

**Subject:** HIPAA/SOC2 teams love this

Hi [First],

If you're in healthcare, fintech, or legal tech, your compliance officer probably has a position on third-party LLMs: "no sensitive data in prompts."

Data Anonymizer gives you the proof. Every anonymization is logged and reversible. Audit trail built in.

Your compliance and product teams can finally move forward together.

[Link]

Wes

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## Email 4: The Real Cost

**Subject:** What's one data breach worth?

Hi [First],

I won't do the math for you. But I'll ask: if your team leaked a customer's SSN or health record through an LLM API, how much would that cost in settlements, remediation, and reputation?

Data Anonymizer costs less than one incident. Often much less.

[Link]

Wes

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## Email 5: Let's Talk

**Subject:** One quick call?

Hi [First],

I've sent a few notes. If any of it resonates, I'd like to understand your current setup: what data flows to LLMs, where the risk lives, what your team already tried.

15 minutes on Thursday or Friday?

[Calendar Link]

Wes