Solutions

PII Detection and Redaction in LLM Outputs

LLMs leak personal data in ways traditional DLP never anticipated: PII pasted into prompts, regenerated in outputs, carried through agent contexts, and embedded in code. By the time a log review finds it, the data has already left. Trussed AI detects and redacts PII in the live path of AI interactions, inspecting prompts and outputs in real time, enforcing masking and redaction policies instantly, and recording every decision for audit.

What is PII detection and redaction for LLMs?

PII detection and redaction for LLMs is the real-time identification of personal information, names, identifiers, contact details, financial and health data, in prompts, model outputs, and agent contexts, with policy-driven actions applied before the data moves: block, mask, redact, tokenize, or log. Done at runtime, it prevents exposure; done after the fact, it only documents it.

Where does PII leak through AI systems?

Inbound prompts, employees and applications submitting customer or patient data to external models
Model outputs, PII regenerated from context or training and returned to unauthorized audiences
Agent workflows, autonomous systems moving personal data across tools and APIs
Code paths, PII embedded in code that AI developer tools read and reproduce
Logs and traces, observability pipelines retaining sensitive content indefinitely

How Trussed AI protects sensitive data

AI Control Plane, centralized runtime governance with data leakage prevention, code-level PII protection, and policy enforcement across apps, agents, and tools.
Runtime privacy actions, inspect prompts and responses in-line; mask, redact, block, or flag per policy, scoped by data class, application, and audience.
Agentic Governance, evaluate sensitive data against policy before any agent action or output is allowed.
AI Audit Assurance, complete records of prompts, outputs, policy decisions, timestamps, and lineage for compliance and audit teams.
Runtime Integrations, proxy-based deployment and SDKs apply PII controls without rewriting applications.
AI Governance Advisory, privacy policy design and operating models for production AI.

Why teams choose Trussed AI for AI data protection

Network DLP can't parse meaning inside an LLM exchange, and provider-side filters enforce the provider's rules, not yours. Trussed enforces your data policies in the interaction itself, HIPAA, GDPR, CCPA, GLBA-aligned, at sub-20ms overhead, with audit evidence generated automatically.

Frequently Asked Questions

Which PII types can be detected? Standard identifiers (names, emails, phone numbers, SSNs, financial accounts), health information, and configurable custom patterns for organization-specific sensitive data.

Can redaction be reversible for authorized users? Policies support graduated actions, full redaction, masking, tokenization, so authorized workflows retain utility while exposure is controlled.

Does this work for AI coding assistants? Yes. Code-aware PII protection covers developer tools, where secrets and personal data in repositories are a major leakage vector.

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