> For the complete documentation index, see [llms.txt](https://docs.nexthink.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.nexthink.com/configuring_nexthink/bringing-data-into-your-nexthink-instance/integrating-nexthink-with-third-party-tools/api-and-integrations-classic/data-enricher-classic.md).
# Data Enricher (classic)
## Overview
The Data Enricher is a software component that complements the information about [users](/references/references-classic/glossary-classic/user-classic.md) and [destinations](/references/references-classic/glossary-classic/destination-classic.md) that Collectors send to the Nexthink Cloud.
[Install the Data Enricher on a Windows Server](/configuring_nexthink/bringing-data-into-your-nexthink-instance/integrating-nexthink-with-third-party-tools/api-and-integrations-classic/data-enricher-classic/installing-data-enricher-classic.md) that is connected to the Active Directory and DNS servers within your corporate intranet.
## Information retrieved
The Data Enricher gets the following information from your servers:
* User information from Active Directory:
* Distinguished Name
* Name
* Full name
* Department
* Job title
* Location
* Locality name
* Country code
* Organizational unit name
* Destination information from reverse DNS lookup:
* Fully Qualified Domain Name
These data are similar to the data retrieved by Engine in an on-premises setup. The user fields Location, Locality name, Country code, and Organizational unit name are however available on Nexthink Experience only.
## Estimated processing time
For an available network bandwidth of 25 Mbps, the following times have been measured for a partial update, with the Data Enricher running on a Windows Server 2016 in an Azure VM (Standard\_F4s - 4 CPU cores, 8 GB memory).
Measured time for retrieving user information from AD:
| Number of users | Duration |
| --------------- | ------------ |
| 500 k | < 7 min |
| 250 k | < 3 min 30 s |
| 100 k | < 1 min 30 s |
| 50 k | < 40 s |
| 20 k | < 20 s |
| 10 k | < 10 s |
| 1 | < 5 s |
Measured time for retrieving the FQDN of destinations from the DNS server:
| Number of destinations | Duration |
| ---------------------- | -------- |
| 500 k | < 20 min |
| 250 k | < 10 min |
| 100 k | < 4 min |
| 50 k | < 2 min |
| 20 k | < 1 min |
| 10 k | < 30 s |
| 1 | < 5 s |
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.nexthink.com/configuring_nexthink/bringing-data-into-your-nexthink-instance/integrating-nexthink-with-third-party-tools/api-and-integrations-classic/data-enricher-classic.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
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.
