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by Ryan Lindsey · 2026-07-24

In regulated industries like legal, healthcare, and finance, the confidentiality of data is paramount. When integrating large language models (LLMs) into your workflows, it's critical to understand how your data is handled. ZC Technologies ensures your prompts are not used as training data, and we operate on owned hardware to provide a secure environment. This post delves into our privacy model and how it supports compliance in sensitive sectors.

ZC Technologies Privacy Model

At ZC Technologies, we prioritize the privacy of your data. Unlike other API providers, we do not log your prompts for training purposes. Our infrastructure is built on dedicated NVIDIA GB10 silicon, ensuring that your data remains on owned hardware, not shared cloud environments. This approach provides a robust layer of security for your sensitive information.

Infrastructure and Compliance

Our ZC Inference Exchange serves Qwen 2.5 models, both 32B and 72B, on dedicated hardware. This setup not only guarantees performance but also ensures that your data is processed in a secure environment. By using our service, you can comply with industry-specific regulations, such as HIPAA in healthcare or GDPR in the European Union, without the risk of data leakage.

Cost-Effective Solutions

We offer competitive pricing that is 60-80% lower per 1M tokens compared to Anthropic and OpenAI. Our subscription plans are designed to meet the needs of various organizations, from startups to large enterprises. Here are the details:

• Starter: $99/mo → 1.5M tokens ($66/1M), models: qwen2.5:32b
• Pro: $499/mo → 12.0M tokens ($42/1M), models: qwen2.5:32b, qwen2.5:72b
• Business: $1999/mo → 60.0M tokens ($33/1M), models: qwen2.5:32b, qwen2.5:72b

Implementation Example

Integrating our API into your application is straightforward. Here's a sample implementation using Python:

import requests

url = 'https://zcx.zctechnologies.org/v1/chat'
headers = {'Authorization': 'Bearer YOUR_BEARER_TOKEN'}
data = {'prompt': 'Your prompt here', 'model': 'qwen2.5:32b'}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Conclusion

For regulated industries, the privacy and security of data are non-negotiable. ZC Technologies offers a secure, compliant, and cost-effective solution for integrating LLMs into your workflows. To start leveraging our services, visit our plans page at https://zcx.zctechnologies.org#plans.