> ## Documentation Index
> Fetch the complete documentation index at: https://pasteguard.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Regulated Teams

> Use AI with sensitive context without sending raw private values to model providers

Regulated teams often want AI help, but the useful context is exactly the context they cannot paste into a third-party provider unchanged.

PasteGuard gives these teams a local or self-hosted privacy layer before requests leave their environment.

## Common Status Quo

Teams usually choose one of these options before adopting a privacy layer:

* Avoid cloud AI for sensitive work
* Redact client or production data manually
* Switch to a local model even when a cloud provider would give better results
* Build one-off masking code inside each app

PasteGuard is designed to replace that manual step with a consistent control point.

## Who It Fits

PasteGuard is useful when sensitive values appear in normal AI work:

* Finance and banking work with customer or transaction context
* Legal and advisory work with privileged or client-confidential material
* Healthcare-adjacent operations with patient or provider details
* Insurance, accounting, consulting, HR, and recruiting work
* Regulated SaaS teams handling logs, support tickets, and production context

## Product Paths

<CardGroup cols={3}>
  <Card title="Browser Chat" icon="comment" href="/use-cases/chat">
    Browser extension beta for ChatGPT, Claude, and Gemini.
  </Card>

  <Card title="Apps & APIs" icon="plug" href="/use-cases/api-integration">
    Apps, SDKs, internal AI products, and provider-compatible APIs.
  </Card>

  <Card title="Coding Agents" icon="code" href="/use-cases/coding-tools">
    Codex, Claude Code, logs, tickets, codebase context, and secrets.
  </Card>
</CardGroup>

## Deployment Model

PasteGuard can run locally for individual use, or self-hosted for team and infrastructure use.

Use local or self-hosted deployment when your team needs tighter control over:

* Where private values are processed
* Which provider receives masked requests
* What request metadata is logged
* How sensitive requests are routed to local models
* How masking rules are configured

<Warning>
  PasteGuard can help keep sensitive values out of prompts before they reach a provider. Your legal, security, and compliance controls still decide whether a workflow is production-ready.
</Warning>

## What To Validate In A Pilot

For a regulated pilot, validate the trust questions before adding more features:

* Can users complete real work without manual redaction?
* Do they understand which values stayed local?
* Do they trust the restoration flow?
* Do they need local, self-hosted, or managed deployment?
* Which logs and audit exports are required before production use?

Start with [Local-First Privacy](/concepts/local-first-privacy), then connect the path your team uses most: [Browser Chat](/use-cases/chat), [Apps & APIs](/use-cases/api-integration), or [Coding Agents](/use-cases/coding-tools).