---
title: "What is an Agent?"
url: "https://dm0bkdes5q7a2ls.productfruits.help/en/article/what-is-an-agent"
language: "en"
last_updated: "2026-10-07T20:01:04.280Z"
---

# What is an Agent?

An Agent is an application installed on a local machine, such as a workstation, or remote virtual machine, that scans and evaluates locations such as files and file shares, OneDrive, Box, SharePoint, etc., for sensitive data such as social security numbers, phone numbers, IMEI numbers, etc.

## Introduction

-   An Agent is an application which scans and evaluates locations (cloud or local) for sensitive data such as social security numbers, credit card numbers, etc.
-   An Agent can be installed on the machine it is scanning or else scan a remote location.
-   Agents operate on behalf of the Spirion Console and send the data they collect back to the Spirion Console to be viewed, analyzed, and acted upon (classified, redacted, quarantined, etc.) by Spirion users.

![](https://cdn-assets.productfruits.com/0af91f13-e95a-42d5-9486-3da994bb79aa)

* * *

## What Problem do Agents Solve?

Agents exist because the console can’t “reach into” every private network, endpoint, or data source directly.

Instead:

-   You instruct Spirion Sensitive Data Platform to define and schedule work
-   The Agent executes work where access to data is possible
-   The pipeline ships results back to the Spirion SaaS services for reporting and governance

Agents solve the practical barriers that stop discovery projects from scaling such as the following:

-   **Network boundaries**: Many Targets (the machines, databases, servers, etc. that you are scanning) live behind firewalls/VPN/proxies.
-   **Authentication realities**: Agents can use approved credentials and permissions close to the data.
-   **Performance and resilience**: Work is queued and processed in stages so transient failures don’t destroy progress.
-   **Operational consistency**: Standardized execution plus standardized logs and evidence for troubleshooting.

* * *

## What are Discovery Agents?

Agents include **Discovery Agents** which act as a group.

-   These Agents may be deployed in large numbers in large environments.
-   This is described in more detail below.

Different Agents are used for different machines or data sources:

-   One Agent scans SQL databases on a remote SQL server, while another scans OneDrive accounts on a cloud location
-   Other Agents scan individual Macbooks or Linux machines

* * *

## Where are Agents shown in Spirion Sensitive Data Platform (UI)?

The individual Agents scanning your environment (workstations, laptops, servers, databases, etc.) for sensitive data are found within the Spirion Sensitive Data Platform user interface on the "Agent Management" page (Agents > Agents).![](https://cdn-assets.productfruits.com/05a2f9c0-0dac-4d98-b155-ccd88774774c)

![](https://cdn-assets.productfruits.com/d099b465-b5ba-4869-9f62-29ca88a593c4)

* * *

## Version 13.6 Windows Agents

Version 13.6 brings a new queueing system to Windows Agents.

-   **PostgreSQL** replaces RabbitMQ, previously used by Agent versions 13-13.5.
-   **pgBouncer**, a lightweight connection pooler for PostgreSQL, replaces Erlang, previously used by Agent versions 13-13.5.
-   The archTIS Spirion Endpoint MSI installation wizard uninstalls both RabbitMQ and Erlang, and all related data, as part of the installation of archTIS Spirion Endpoint v13.6
-   -   For more information, see [How to Create the MSI Installation Package](https://dm0bkdes5q7a2ls.productfruits.help/en/article/working-with-installations#how-to-create-the-msi-installation-package)

* * *

## When and How to Use Agents

Agents are managed from the **Agent Management** page.

-   Agent Management page: To navigate to the Agent Management page, from the left side navigation menu select **Agents**.  
      
    ![](https://cdn-assets.productfruits.com/623682a7-85ec-40c2-88da-4217c7178b3c)  
    
-   1 or more Agents can be collected into a single Agent **Tag**.
-   -   Tags are managed from the **Tag Management** page (Data Asset Inventory>Tag Management from the home screen)

You can perform the following actions with Agents:

-   View Agents
-   View Agent names, status, last heartbeat, and policy
-   Assign Policies to Agents
-   Remove Agents
-   Manage Agent Tags (organizational labels)
-   Bulk Assign Tags (organizational labels) to Agents
-   Bulk Assign Policies to Agents

* * *

## Function and Purpose

-   **Location**: Agents are installed either locally or remotely on a VM
-   **Function**: Agents evaluate and scan locations (such as OneDrive, SQL servers, laptops, etc.) for sensitive data.
-   -   Agents perform their scanning and evaluation function by following an Agent Policy.
    -   -   An **Agent Policy** is a set of rules for the Agent to follow.
        -   For more on creating and working with policies, see [Working with Policies](https://dm0bkdes5q7a2ls.productfruits.help/en/article/new-article-116)
    -   Agents are typically installed on a Windows, Mac or Linux desktop, server, or virtual machine (VM).
    -   -   Agents installed on a single desktop (to scan that individual desktop), act as both an **Agent** and a **Target**. For more information about Targets, see [What is a Target?](https://dm0bkdes5q7a2ls.productfruits.help/en/article/what-is-a-target)
    -   Agents do the actual scanning of the source system files.
    -   Agents connect to the source or Target (OneDrive, SharePoint, box, etc.) to be scanned and access the files and their contents.
    -   Multiple Agents scan the same source, in parallel, each Agent scanning a separate file at a time
    -   **Agent Scanning**:
    -   -   Agents act in tandem
        -   -   One Agent acts as a "discovery Agent," and discovers the files to be scanned in the source system
            -   One or more additional "search Agents" scan the source system files for sensitive data.
        -   The more Agents you run, the faster your data is scanned
        -   Each Agent can scan approximately 1.8 GB of data per hour or 40-75 GB of data per day (24 hours)
    -   A **Discovery Team** is composed of a minimum of 3 Agents
    -   -   Spirion recommends running a minimum of 10 Agents for speed and efficiency
        -   The first initial scan of your source systems can take several weeks
        -   Follow-up scans can be completed in a day or less, as Sensitive Data Platform scans only those files that have a changed state (see [Differential Scanning](https://dm0bkdes5q7a2ls.productfruits.help/en/article/what-is-differential-scanning))

![Interconnected Spirion components sending inbound and outbound data](https://cdn-assets.productfruits.com/a3caeb34-288b-463f-a210-bed535d58072)

## Example: 10 Agent Deployment

There can be 10 Agents configured in a single scan, scanning a single source or Target (OneDrive, Google Drive, remote machine, local machines, Oracle, etc.).

-   One of those 10 Agents is designated as the "discovery" Agent
-   -   The role of this Agent is to enumerate through the source to find all files that will need to be scanned.
    -   While enumerating through the source, the discovery agent is adding all of those files to a job queue (Managed by PostgreSQL (v13.6+) or RabbitMQ (v13-13.5).
-   The other 9 Agents participate in the scan, now designated as "search" Agents
-   -   These Agents do the following:
    -   -   Act in parallel for speed and efficiency
        -   Access the job queue on the discovery Agent machine
        -   Pull the next job in line, which contains all of the info about the files each must scan.
        -   Each search Agent pulls one "job" from the job queue at a time
        -   Each search Agent searches only the locations (files or emails) listed in that job
    -   All 9 search Agents search different files from the same source at the same time.
    -   There can be multiple Agents connecting to and accessing files in a source, but only a single file is scanned by a single Agent at a given time.

![Local and cloud data sources connected to Spirion console/database/operators](https://cdn-assets.productfruits.com/8625a61f-eddd-49b0-a402-f30a9342c150)
