Protect sensitive data by deploying client-side regex and NER (Named Entity Recognition) redaction filters that mask credit cards, Social Security numbers, passwords, and PII before text is transmitted to the LLM, combined with zero-retention enterprise API agreements that prohibit training on user conversations.
AI聊天中意外PII暴露的关键风险
No matter how many warnings you put on your website stating 'Please do not share sensitive credentials', customers will inevitably paste full credit card numbers, account passwords, Social Security numbers, and confidential medical details directly into your support chat box when describing an issue.
If your AI chatbot transmits this un-sanitized text to third-party language models or stores it in unencrypted vector databases, your company faces severe regulatory and security penalties under GDPR, HIPAA, CCPA, and PCI-DSS.
企业数据隐私需要主动、多层的安全架构:
- Edge-Level PII Scrubbing: Before a user's prompt leaves the browser or hits the LLM, regex pattern matchers and privacy filters automatically detect and replace sensitive entities (e.g. converting `4111-2222-3333-4444` to `[REDACTED_CREDIT_CARD]`).
- Zero-Data-Retention (ZDR) Agreements: Ensuring all enterprise AI API calls operate under strict contractual guarantees that customer inputs are processed ephemerally in RAM and never used to train foundational AI models.
- End-to-End Encryption: Encrypting all chat logs at rest (AES-256) and in transit (TLS 1.3), with automated retention policies that purge historical logs after 30 to 90 days.
| 隐私向量 | 标准DIY AI包装器 | Seatext企业隐私架构 |
|---|---|---|
| 信用卡和SSN处理 | 以原始文本传输到外部API | 客户端正则表达式在发送前自动脱敏 |
| 用户提示用于模型训练 | 通常选择加入公共模型训练 | 严格的零数据保留(ZDR)保证 |
| GDPR“被遗忘权” | 手动数据库搜索/删除 | 一键自动删除客户数据 |
| 加密标准 | 基本HTTPS | 静态AES-256加密 + 传输TLS 1.3 |
实施全面的支持隐私防护盾
- Deploy Client-Side Entity Redaction: Intercept form inputs with client-side filters targeting 16-digit card numbers, CVVs, and password strings.
- Verify Enterprise Zero-Retention Terms: Ensure all underlying AI infrastructure providers contractually guarantee that your customer data is never used for model training.
- Implement Role-Based Access Control (RBAC): Restrict access to chat transcripts so only authorized support agents can inspect sensitive conversations.
- Enforce Automated Data Retention Limits: Configure automated cron jobs to purge customer chat transcripts and IP records after 30, 60, or 90 days.
常见问题
客户对话数据是否用于训练AI模型?
绝不。Seatext在企业零数据保留条款下运营。你的客户对话、提示和专有数据均被临时处理,绝不共享或用于模型训练。
Seatext如何处理GDPR删除请求?
你可以通过我们的仪表板或删除API,立即清除任何用户在所有数据库中的对话历史,以保持100%的GDPR合规性。
我们能否在特定地理区域(例如,仅限欧盟)托管Seatext?
可以。企业客户可以将流量路由到专用的欧盟或美国数据中心,以遵守当地数据主权要求。
