Hybrid VPC: Deploy an Enterprise AI Firewall Where Prompts Never Leave Your Network

The conversation in every enterprise security review meeting sounds the same:

“We want to use GPT-4 and Claude in our applications. But our compliance team says prompt data can't leave our network. What are our options?”

Until now, the options were binary: use a cloud AI gateway and accept that prompts transit through a third-party proxy, or build your own governance stack from scratch. The first option fails compliance reviews. The second takes 6-12 months and a dedicated engineering team.

Hybrid VPC is the third option. A compiled Go proxy that runs inside your network — handling DLP scanning, PII redaction, prompt injection blocking, and budget enforcement locally — while a cloud dashboard manages policies and displays metadata-only analytics.

Cloud AI gateways solve the governance problem — they scan prompts for PII, enforce budgets, block injections, and log everything. But they require your prompt data to pass through their servers. For many enterprises, that's a non-starter:

• ✗Healthcare (HIPAA) — patient data in prompts can't transit third-party infrastructure
• ✗Financial services (SOX/PCI) — cardholder data and financial records must stay within the compliance boundary
• ✗Government / defense — classified or sensitive data has strict data residency requirements
• ✗Legal — attorney-client privilege demands that case details never leave firm infrastructure

Self-hosting an open-source AI proxy solves the data sovereignty problem, but you lose the governance layer: no dashboards, no centralized policy management, no violation tracking, no budget enforcement. You're back to building from scratch.

Hybrid VPC splits the AI firewall into two zones:

The critical guarantee: prompt and response content never leaves your network. The proxy processes everything locally and forwards cleaned requests directly to your AI provider (OpenAI, Anthropic, Google, etc.). The sync agent pushes only structural metadata to the cloud — token counts, latency measurements, entity type counts, and cost estimates. Content fields are rejected server-side.

The hybrid proxy is OpenAI SDK compatible. Point your base URL to the proxy and use your project API key:

from openai import OpenAI

client = OpenAI(
    base_url="http://hybrid-proxy:8080/v1",  # Your local proxy
    api_key="oah_your_project_api_key",
)

# Every request is now DLP-scanned, budget-checked,
# and logged — without any data leaving your network
response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[{"role": "user", "content": "Analyze this contract..."}],
)

That's it. No SDK changes, no middleware, no code annotations. Every request flowing through the proxy is automatically scanned for 30+ PII entity types, checked against your project's DLP policy, and budget-verified — all before the request reaches your AI provider.

Hybrid VPC is designed for organizations that need full AI governance but can't send prompt data through a third-party cloud proxy:

• Enterprises in regulated industries (healthcare, finance, legal, government)
• Organizations with strict data residency requirements
• Teams that need to demonstrate data sovereignty for compliance audits
• Companies deploying AI in environments with restricted outbound network access
• Security-conscious organizations that want defense-in-depth for AI workloads

Hybrid VPC is available on the Enterprise plan. Here's how to get started:

1. 1Contact us at enterprise@aisecuritygateway.ai to enable Hybrid VPC on your account
2. 2We provision your deployment token and container registry access
3. 3You deploy three Docker containers in your VPC using our Docker Compose template
4. 4You point your app's base URL to the proxy — two lines of code