Freshdesk is a cloud-based customer support platform from Freshworks. It lets teams manage tickets across email, chat, phone, and social channels, track SLAs, and coordinate work between agents and groups. This connector extracts your Freshdesk help desk data so you can analyze ticket volume, agent performance, response times, and customer relationships.

Configuring Freshdesk as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Freshdesk option from the list of connectors. Click Next and you’ll be prompted to add your access.

1. Add account access

You’ll need your Freshdesk subdomain and API key to authenticate. Freshdesk uses HTTP Basic authentication with the API key as the username.

Obtaining Your API Key

Open your profile

Click your profile picture in the top-right corner and select Profile settings.

Copy the API key

On the right side of the profile page, click View API Key and copy the value.

Store your API key securely. Treat it like a password and do not share it publicly.

Configuration Fields

The following configurations are available:

Freshdesk domain: Your Freshdesk subdomain. For an account hosted at https://acme.freshdesk.com, this value is acme.
API key: The API key copied from your Freshdesk profile page.
Start date: The earliest date from which records will be synced. This controls the initial window for the tickets, contacts, and companies streams.

Once you’re done, click Next.

2. Select streams

Choose which data streams you want to sync. For faster extractions, select only the streams that are relevant to your analysis.

Tip: The stream can be found more easily by typing its name.

Select the streams and click Next.

3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table, and the type of sync.

Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster.
Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
- Incremental: every time the extraction happens, we’ll get only the new data, which is good if you want to keep every record ever fetched.
- Full table: every time the extraction happens, we’ll get the current state of the data, which is good if you don’t want to have deleted data in your catalog.

Once you are done configuring, click Next.

4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often you want data to be extracted from this source. Ticket data typically benefits from hourly or daily refreshes depending on your support volume. Optionally, you can determine when to execute an Additional Full Sync. This complements incremental extractions and ensures your data is fully synchronized every once in a while. Once you are ready, click Next to finalize the setup.

5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.

For you to be able to see it on your Catalog, you need at least one successful source run.

Streams and Fields

Below you’ll find all available data streams from Freshdesk and their corresponding fields:

Tickets

Stream containing all support tickets, the central fact table for help desk analytics. Supports incremental sync based on the updated_at field. The stream automatically includes ticket stats (response and resolution timestamps) via the include=stats parameter for SLA analysis.

Field	Type	Description
`id`	Integer	Unique ticket ID
`subject`	String	Ticket subject
`description_text`	String	Plain-text description
`type`	String	Ticket type (e.g., Question, Incident, Problem, Feature Request)
`status`	Integer	Status code: 2=Open, 3=Pending, 4=Resolved, 5=Closed
`priority`	Integer	Priority: 1=Low, 2=Medium, 3=High, 4=Urgent
`source`	Integer	Source channel (email, portal, phone, chat, etc.)
`spam`	Boolean	Whether the ticket is marked as spam
`requester_id`	Integer	Contact who created the ticket
`responder_id`	Integer	Agent assigned to the ticket
`company_id`	Integer	Associated company
`group_id`	Integer	Assigned agent group
`product_id`	Integer	Product associated with the ticket
`email_config_id`	Integer	Email mailbox used
`fr_escalated`	Boolean	Whether first response SLA was breached
`is_escalated`	Boolean	Whether resolution SLA was breached
`fr_due_by`	DateTime	First response due-by timestamp
`due_by`	DateTime	Resolution due-by timestamp
`nr_due_by`	DateTime	Next response due-by timestamp
`nr_escalated`	Boolean	Whether next response SLA was breached
`tags`	Array	Ticket tags
`cc_emails`	Array	CC emails on the ticket
`fwd_emails`	Array	Forwarded emails
`reply_cc_emails`	Array	Reply CC emails
`to_emails`	Array	To emails on the ticket
`due_by_in_hours`	Number	Due-by in hours
`sentiment_score`	Number	Latest sentiment score
`initial_sentiment_score`	Number	Initial sentiment score
`custom_fields`	Object	Account-specific custom fields
`stats.agent_responded_at`	DateTime	Last agent response timestamp
`stats.requester_responded_at`	DateTime	Last requester response timestamp
`stats.first_responded_at`	DateTime	First agent response timestamp
`stats.status_updated_at`	DateTime	Last status change timestamp
`stats.reopened_at`	DateTime	Reopen timestamp
`stats.resolved_at`	DateTime	Resolution timestamp
`stats.closed_at`	DateTime	Closure timestamp
`stats.pending_since`	DateTime	Pending-since timestamp
`created_at`	DateTime	Creation timestamp
`updated_at`	DateTime	Last update timestamp

Conversations

Stream containing ticket replies and private notes, fetched per ticket from the /tickets/{ticket_id}/conversations endpoint. Use this stream to analyze response times, interaction counts, and the full conversation timeline for each ticket.

Field	Type	Description
`id`	Integer	Unique conversation ID
`ticket_id`	Integer	Parent ticket ID
`user_id`	Integer	Author (agent or contact) user ID
`from_email`	String	Sender email
`to_emails`	Array	To email addresses
`cc_emails`	Array	CC email addresses
`bcc_emails`	Array	BCC email addresses
`body_text`	String	Plain-text message body
`incoming`	Boolean	Whether the message is incoming (from customer)
`private`	Boolean	Whether this is a private note (agent-only)
`source`	Integer	Source channel for the conversation
`support_email`	String	Support email address used
`category`	Integer	Conversation category
`thread_id`	Integer	Thread ID for threaded conversations
`thread_message_id`	Integer	Thread message ID
`last_edited_at`	DateTime	Last edit timestamp
`last_edited_user_id`	Integer	User who last edited
`attachments`	Array	Attachment objects (id, name, content_type, size, attachment_url, timestamps)
`created_at`	DateTime	Creation timestamp
`updated_at`	DateTime	Last update timestamp

Contacts

Stream containing all customers who have submitted tickets or been added to the help desk. Supports incremental sync based on the updated_at field.

Field	Type	Description
`id`	Integer	Unique contact ID
`name`	String	Contact name
`email`	String	Primary email
`phone`	String	Phone number
`mobile`	String	Mobile number
`job_title`	String	Job title
`address`	String	Address
`description`	String	Contact description
`language`	String	Preferred language
`time_zone`	String	Time zone
`twitter_id`	String	Twitter handle
`facebook_id`	String	Facebook ID
`unique_external_id`	String	External ID from integrated systems
`active`	Boolean	Whether the contact is verified/active
`blocked`	Boolean	Whether the contact is blocked
`blocked_at`	DateTime	Block timestamp
`deleted`	Boolean	Whether the contact is soft-deleted
`company_id`	Integer	Primary company association
`view_all_tickets`	Boolean	Whether contact sees all company tickets
`tags`	Array	Contact tags
`other_emails`	Array	Additional emails
`other_phone_numbers`	Array	Additional phone numbers
`other_companies`	String	Secondary companies linked to this contact (JSON)
`custom_fields`	String	Account-specific custom fields (JSON)
`created_at`	DateTime	Creation timestamp
`updated_at`	DateTime	Last update timestamp

Companies

Stream containing organizations that group contacts, commonly used for B2B support. Supports incremental sync based on the updated_at field.

Field	Type	Description
`id`	Integer	Unique company ID
`name`	String	Company name
`description`	String	Company description
`note`	String	Internal note
`domains`	Array	Email domains associated with the company
`health_score`	String	Customer health score
`account_tier`	String	Account tier (e.g., Premium, Basic)
`renewal_date`	DateTime	Contract renewal date
`industry`	String	Industry
`custom_fields`	String	Account-specific custom fields (JSON)
`created_at`	DateTime	Creation timestamp
`updated_at`	DateTime	Last update timestamp

Agents

Stream containing all support agents with their roles, groups, and skills. Extracted as a full-table sync.

Field	Type	Description
`id`	Integer	Unique agent ID
`available`	Boolean	Whether the agent is currently available
`available_since`	DateTime	Timestamp since current availability state
`occasional`	Boolean	Whether the agent is occasional (non-full-time)
`signature`	String	HTML signature
`ticket_scope`	Integer	1=Global, 2=Group, 3=Restricted access
`type`	String	Agent type (support_agent, field_agent, collaborator)
`focus_mode`	Boolean	Whether focus mode is enabled
`deactivated`	Boolean	Whether the agent has been deactivated
`last_active_at`	DateTime	Last active timestamp
`group_ids`	Array	Groups the agent belongs to
`role_ids`	Array	Roles assigned to the agent
`skill_ids`	Array	Skills assigned to the agent
`contact`	String	Embedded user/contact record for the agent (JSON)
`created_at`	DateTime	Agent record creation timestamp
`updated_at`	DateTime	Agent record last update timestamp

Data Model

The following diagram illustrates the relationships between the core data streams in Freshdesk. The arrows indicate the join keys that link the different entities.

Implementation Notes

Data Sync Considerations

Incremental sync: Tickets, contacts, and companies support incremental sync based on updated_at. Agents and conversations are extracted as full-table syncs.
Ticket stats: The tickets stream automatically requests the stats block from the Freshdesk API, giving you response and resolution timestamps without a second API call.
Conversations: Conversations are nested under tickets. Any ticket included in a sync will have its conversations re-fetched, so keep this in mind when tuning the start date for high-volume accounts.

API Limits & Performance

Page cap: The Freshdesk list endpoints cap at 300 pages of 100 records (30,000 records per filter window). For accounts exceeding this, use a recent start date and increase the sync frequency so each incremental window stays within the cap.
Rate limits: Freshdesk enforces per-minute rate limits that vary by plan. The connector retries on 429 responses using the Retry-After header.
Timestamps: All timestamps are returned in UTC (ISO 8601).

Skills for agents

Download Freshdesk skills file

Freshdesk connector documentation as plain markdown, for use in AI agent contexts.

​Configuring Freshdesk as a Source

​1. Add account access

​Obtaining Your API Key

​Configuration Fields

​2. Select streams

​3. Configure data streams

​4. Configure data source

​5. Check your new source

​Streams and Fields

​Data Model

​Implementation Notes

​Data Sync Considerations

​API Limits & Performance

​Skills for agents

Download Freshdesk skills file

Configuring Freshdesk as a Source

1. Add account access

Obtaining Your API Key

Configuration Fields

2. Select streams

3. Configure data streams

4. Configure data source

5. Check your new source

Streams and Fields

Data Model

Implementation Notes

Data Sync Considerations

API Limits & Performance

Skills for agents