Sensitive data protection for generative AI

Control what goes into your AI—
and what comes out.

Detect and de-identify sensitive information across documents, images, prompts, responses, and logs. Apply security policies, block risky requests, and keep an audit trail of policy actions.

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Use sensitive data with
the controls it requires.

Blocking every request limits what teams can do. Allowing every request creates exposure. DocuSafety lets you apply rules for when information is allowed, de-identified, or blocked.

Protect sensitive data
as AI use expands

DocuSafety is more than a filter. It provides the controls and oversight needed to use generative AI in day-to-day work.

Documents and images, not just text

Find sensitive information in documents and images, including text captured from scanned pages.

De-identified data you can still use

Rather than blocking data outright, de-identify it so approved teams can search, summarize, and analyze it.

API integration

Connect DocuSafety to the generative AI applications you already run through the API.

Logs, monitoring, policies, and audits

Keep de-identification history, inputs, and allow/block decisions in one place to support oversight and audit reviews.

Three core capabilities

  1. Identify and de-identify sensitive information

    Process documents and images before they are searched, shared, or used with AI.

    Detect personal and confidential information in documents and images. Apply masking, substitution, or pseudonymization according to policy, and retain metadata about the processed data.

    • Detection of personal information in documents and images
    • Masking, substitution, and pseudonymization
    • De-identification of text extracted with OCR (optical character recognition)
    • Processed results with metadata on detected PII types
  2. Inspect AI inputs and responses

    AI DLP (data loss prevention) checks what is sent to a model and what comes back.

    Check prompts, attachments, and model responses for sensitive information and policy violations. Detect and block prompt-injection and data-exfiltration attempts.

    • Sensitive data controls before a request reaches the model
    • Prompt injection detection and blocking
    • Protection against data-exfiltration attempts
    • Blocked requests listed with the policy behind each one
  3. Manage policies and review activity

    Oversee usage, alerts, and policy decisions from a central console.

    Set security policies, monitor usage, and investigate alerts. Review requests, blocked activity, and processing history through centralized logs.

    • Central security policy management
    • Real-time monitoring of prompts, responses, and logs
    • Anomalous usage detection and alerts
    • Audit logs of policy actions and usage statistics
  1. Add data protection
    to your existing
    AI workflows.

    Route supported AI requests through DocuSafety to apply sensitive data detection, de-identification, policy checks, and response processing. Integrate with existing chatbots, RAG (retrieval-augmented generation) applications, AI agents, and business systems through the API.

For teams managing sensitive information and AI access

Prepare sensitive data for analysis

Process personal information in forms, contracts, reports, and service records before using the data for approved analysis and AI tasks.

Govern AI use across departments

Apply policies to prompts and responses, monitor activity, and review how sensitive information is handled.

Apply different rules to different groups

Configure access and policy controls to reflect the responsibilities of each team or role.

What changes with DocuSafety

  1. 01

    Pseudonymized data and generative AI governed by the same policies

  2. 02

    Lower risk of exposing personal and confidential information

  3. 03

    Earlier detection of prompt injection and unusual usage

  4. 04

    Visibility into operations through audit logs and policy history

  5. 05

    Clear rules that help staff use AI with confidence

Frequently asked questions

What data does DocuSafety protect?

DocuSafety covers documents, images, prompts, responses, and logs. It detects personal and confidential information in each, and manages de-identification, blocking, monitoring, and audit logs of policy actions in one place.

Can pseudonymized data be used in AI work?

Yes, within the rules your policies set. Instead of blocking data outright, DocuSafety identifies personal and sensitive information in documents and images, applies masking, substitution, or pseudonymization according to policy, and returns the processed results with metadata for search, summarization, and analysis. Pseudonymized data can still be sensitive, so access and use remain subject to your policies.

Can it work with the generative AI and chatbots we already use?

Yes. DocuSafety integrates with existing chatbots, RAG (retrieval-augmented generation) applications, AI agents, and business systems through the API. Supported AI requests are routed through DocuSafety for sensitive data detection, de-identification, policy checks, and response processing, while users keep working in the tools they already know. Our team can review the integration scope for your systems.

Does it also stop attacks like prompt injection?

Yes. DocuSafety detects and blocks malicious inputs such as prompt injection, along with attempts to extract internal information. It also controls whether sensitive or pseudonymized information can reach a model under your policies. Blocked requests are logged with the policy reason for each.

How do we monitor usage and anomalies?

From a central console. Administrators manage security policies, monitoring and alerts, AI anomaly detection, log analysis, and usage statistics in one place. De-identification history, input history, and allow/block decisions are recorded together to support oversight and audit reviews.

Can different departments or groups have different policies?

Yes. Security policies are managed centrally, and access and policy controls can be configured by group to reflect the responsibilities of each team or role.

Make data protection part of your AI workflow

Talk to us about the data you handle, the AI systems you use, and the controls you need.

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