LLM gateway for regulated industries handling sensitive data

AIThis description was written by a model from public signals. The facts behind it are listed under Evidence.

Problem

Companies in aerospace, defense, and other highly regulated industries need to use AI tools but cannot trust commercial AI platforms with sensitive data due to ITAR, CUI, and FedRAMP compliance requirements. They lack a compliant infrastructure layer that allows them to use modern AI models while maintaining data protection and passing security assessments.

Solution concept

A compliant LLM gateway that sits between users and AI model providers, enforcing compliance policies and routing requests only to government-approved infrastructure. It provides a single OpenAI-compatible endpoint that abstracts away cloud provider complexity, requires compliance suffixes on model names, verifies API keys and organizational identity, and maintains zero data retention while allowing per-user spend and model restrictions.

Who has it

Aerospace and defense companies, government contractors, and organizations handling ITAR-restricted or controlled unclassified information (CUI), ranging from small teams to large enterprises.

How they handle it today

Today, regulated companies either avoid AI tools entirely (even for non-sensitive work) due to compliance concerns, or manually manage separate accounts across multiple government cloud environments (AWS GovCloud, Azure Government, etc.), each with different available models and compliance controls. They must choose between cloud providers rather than selecting based on data control requirements and desired AI models.

Why now

Rapid AI adoption and the emergence of frontier models over the past 9-12 months have created urgent demand, but aerospace and defense companies remain blocked by compliance risk and data protection fears. Government cloud availability has improved but remains fragmented across providers and models.

How it could charge