The Problem
The gap in your AI governance framework.
Most enterprise AI governance programs cover model risk and data access. Almost none of them enforce your communication policies on what AI agents actually say.
Your AI makes unsupported claims
A sales copilot promises a feature that doesn't exist. An automated proposal overstates your capabilities. The customer relies on it. Your legal team finds out in discovery.
Your AI creates regulatory exposure
An AI assistant sends a forward-looking statement during your quiet period. A chatbot discloses MNPI. An automated email violates Reg BI. These aren't hypothetical — they're the violations regulators are already asking about.
Your AI policy lives in a document
Your acceptable use policy says "AI agents must comply with company communications policies." That's the requirement. But there's no technical mechanism to make it happen.
How It Works
Policy enforcement at the AI layer.
InPolicy's API and MCP server extend your policy library to AI-generated outputs — the same policies that govern humans, applied to the new layer of communications your company is now producing.
Policy injection at inference time
InPolicy injects your structured policy library into the AI agent's context before it generates a response — so the agent reasons about your policies while composing, not after.
The same policies that govern humans
No separate AI policy layer. The same communication policies that govern what your employees write also govern what your AI agents write. One library, enforced consistently.
API and MCP server integration
Route AI-generated outputs through InPolicy's policy enforcement layer before delivery. Works with any model — GPT-4, Claude, Gemini, or your own fine-tuned model.
Conversational context awareness
Policy violations often only make sense in the context of a thread. InPolicy's enforcement understands conversation history, not just isolated messages.
Roadmap
Start with humans.
Extend to agents.
InPolicy enforces your communication policies for human employees today — in email, chat, and documents, via a browser extension. The API and MCP server (on early-access waitlist) extend the same policy layer to AI-generated outputs.
One policy library. Enforced consistently across everything your company communicates — regardless of whether it was written by a person or generated by an AI.
One policy layer — for everyone
Human employee
Enforced via browser extension
Google Docs agent
Enforced via Policy Bot
AI sales copilot
Enforced via API / MCP
Automated email AI
Enforced via API / MCP
Get your AI agents in-policy.
Tell us which AI systems you're deploying — we'll walk you through how InPolicy's enforcement layer integrates with your stack.