# Infrastructure

NTT DATA Syntphony Conversational AI harnesses the power of industry-leading cloud service providers, Google Cloud Platform (GCP) and Microsoft Azure, known for their scalable, secure, and dependable cloud solutions. These platforms are fortified with robust physical and digital security protocols to fortify your data against potential threats. Through the utilization of GCP and Azure's security measures and compliance certifications, we ensure that our conversational AI solution is delivered with the utmost security and peace of mind to our valued customers."

GCP and Azure employ industry-leading security controls and are extensively audited. Both hold multiple certifications, including SOC2 Type II, ISO 27001, and PCI. For more information about their security practices, see below:

{% embed url="<https://cloud.google.com/security>" %}
GCP Trust Center
{% endembed %}

{% embed url="<https://www.microsoft.com/en-us/trust-center>" %}
Azure Trust Center
{% endembed %}

### Multi-Tenant Architecture <a href="#multi-tenant-architecture" id="multi-tenant-architecture"></a>

All Customer data is stored within the eva cloud systems. Data submitted to eva are processed and stored in a secure, in a multi-tenant environment. Logical and Physical segmentation, such as having separate databases, schemas, or namespaces for each customer, are used to prevent co-mingling of customer data.

ISO 27001 - Data Center

SOC 2 Type I - Data Center

SOC 2 Type II - Data Center (<https://cloud.google.com/security/compliance/soc-2>)

SOC 3 - Data Center

PCI DSS - <https://cloud.google.com/security/compliance/pci-dss?hl=es>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.conversational-ai.syntphony.com/user-guide/security-and-compliance/infrastructure.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.