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---
title: AI meets privacy: ngrok's secure bridge to customer data
description: A walkthrough of deploying AI workloads directly into a customer's virtual private cloud using a Bring Your Own Cloud (BYOC) architecture, with ngrok acting as...
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og:description: A walkthrough of deploying AI workloads directly into a customer's virtual private cloud using a Bring Your Own Cloud (BYOC) architecture, with ngrok acting as...
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# AI meets privacy: ngrok's secure bridge to customer data

**[ngrok Blog](https://daily.dev/sources/ngrok)** · 11 min read · 0 upvotes · 0 comments

## Summary

A walkthrough of deploying AI workloads directly into a customer's virtual private cloud using a Bring Your Own Cloud (BYOC) architecture, with ngrok acting as a secure tunneling layer between a SaaS control plane and the customer's data plane. Covers setting up ngrok's Kubernetes Ingress Controller, custom wildcard domains, authtoken scoping, IP restrictions, and route fanout, using a containerized Ollama service as an illustrative (non-production) example of exposing AI APIs without moving customer data out of their infrastructure.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://ngrok.com/blog/ai-meets-ngrok-privacy-customer-data>

## Questions this post answers

### What is a Bring Your Own Cloud (BYOC) architecture in the context of AI SaaS products?

BYOC architecture means deploying your service into a customer's own cloud data plane to process their data locally, while your SaaS platform acts as the control plane coordinating what gets analyzed and displaying results. This avoids egressing sensitive customer data out of their infrastructure, reduces compliance risk, and shifts most compute costs onto the customer's own cloud resources. Databricks is a well-known example of a platform using this model.

_daily.dev surfaces architecture patterns like BYOC for teams designing customer-data-sensitive AI products._

### How can I expose a Kubernetes service running in a customer's VPC securely without opening inbound firewall ports?

Install the ngrok Kubernetes Ingress Controller via Helm on the customer's cluster and configure it with a customer-specific ngrok Authtoken scoped to a wildcard domain. Ngrok's agent creates an outbound-only secure tunnel to ngrok's Cloud Edge, automatically provisioning HTTPS edges for your routes, so no inbound firewall changes or lengthy NetOps approvals are required.

_developers wiring up secure cross-network tunnels can track ngrok workflow guides on daily.dev._

### Why shouldn't customer data be uploaded to a vendor's own cloud for AI processing instead of using BYOC?

Customers typically refuse to egress their data due to regulatory and governance obligations, and the transfer costs of moving large datasets between clouds can outweigh the value the AI service provides. Running the AI workload inside the customer's own VPC instead avoids both the compliance risk and the data-transfer expense, while still letting the vendor's control plane orchestrate and view results remotely.

_teams weighing data residency trade-offs in AI product design can find related architecture writeups on daily.dev._

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---

Tags: [#devtools](https://daily.dev/tags/devtools), [#kubernetes](https://daily.dev/tags/kubernetes), [#data-privacy](https://daily.dev/tags/data-privacy), [#ollama](https://daily.dev/tags/ollama)

[View this post on daily.dev](https://daily.dev/posts/ai-meets-privacy-ngrok-s-secure-bridge-to-customer-data-yoljdkij9)

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