# Out-of-the-box Detector Library: 13 sensitive-data categories on day one

> The Out-of-the-box Detector Library delivers 13 categories of sensitive-data coverage from day one, making strong privacy the default rather than a build.

**Category:** PII & Sensitive Data
**Author:** NeuralSeek Team · **Published:** June 9, 2026
**Canonical:** https://neuralseek.ai/ai-grounded/pii-detector-library
**Section index:** https://neuralseek.ai/ai-grounded

Out-of-the-box Detector Library is one of NeuralSeek's PII & Sensitive Data guardrails — part of the platform's 118 individually configurable, fully auditable controls. In regulated, high-volume AI, the difference between a system you can trust and one you merely hope works comes down to specific, tunable controls exactly like this one. Here is what Out-of-the-box Detector Library does, why it matters to the business, and how to set it for your own environment.

## What it actually does

This is the built-in library of 13 detector categories — names, cards, addresses, SSNs, emails, credentials, and more — available the moment you start. There's no model to train or integration to build.

## Why business teams care

Most teams need broad privacy coverage immediately, not after a long detector-building project. A comprehensive out-of-the-box library means strong protection is the default rather than a roadmap item.

## How to tune it in practice

Enable the detectors relevant to your data and pair them with custom patterns for anything domain-specific. Review coverage against the categories of data you actually handle.

## Common failure modes it prevents

Data leaks are among the most expensive and least forgivable AI failures, and they happen the instant unmasked personal information reaches a model or a log. Out-of-the-box Detector Library closes that gap directly. By making the behavior an explicit, enforced control rather than something left to chance, it converts a latent risk into a managed, observable event — one that surfaces in the audit trail instead of in a customer complaint or a compliance finding.

## Where it fits in the stack

It operates as a privacy perimeter around the model, screening content on the way in and on the way out. Because it lives in NeuralSeek's governance layer rather than inside any single model, the control holds identically whether a request routes to OpenAI, Anthropic, Gemini, Llama, Mistral, IBM watsonx, or an in-house model.

## Privacy that scales with the business

Configured once per tenant, this control protects personal data uniformly across every channel and workflow, so privacy stops being a per-project scramble and becomes a property of the platform.

> Privacy protection shouldn't start with a six-month detector project.

## The takeaway

The Out-of-the-box Detector Library delivers 13 categories of sensitive-data coverage from day one, making strong privacy the default rather than a build.

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From NeuralSeek's AI Grounded — practical, web-verified guidance on building governed, grounded enterprise AI. NeuralSeek is the model-agnostic, governed AI platform you own: any LLM (swap with no rebuild), your data in your own tenant (cloud or on-prem), 118 guardrails enforced before any action, one container that runs anywhere.