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RD Station Conversas is RD Station’s conversation and messaging platform for managing customer interactions across channels (WhatsApp, Instagram, email, and others). The connector extracts contacts, message history, flows, templates, and related data from the Conversas API so you can centralize conversation data in your Lakehouse.

Configuring RD Station Conversas as a Source

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

1. Add account access

You’ll need to provide authentication so Nekt can access your RD Station Conversas data. The API uses a JWT sent in the Authorization: Bearer header. The following configurations are available:
  • Access token: Token used for authentication. Required. You can get it at Apps & Integrations > API > RD Station Conversas (developers.rdstation.com).
  • Private key (JWK) for decryption: JWK (JSON Web Key) of the private key as a JSON string, to decrypt messages history responses. Optional. Generate it at Apps & Integrations > API > Generate Key. See Conversas v2 encryption. If not provided, message history is stored as encrypted payload in the data field.
  • Start date: Start date for fetching historical messages. Required if using the messages history stream. Only messages from this date onward are fetched. You can use common date formats (e.g. 2024-01-01).
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. You can select entire groups of streams or pick specific ones.
Tip: The stream can be found more easily by typing its name.
The messages_history stream is a child of contacts: it fetches conversation history per contact. Selecting messages_history will sync history for every contact. Ensure Start Date is set if you use this stream. This stream is available only on the Advanced plan — see planos RD Station Conversas.
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 (which will effectively contain the fetched data) 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: all streams in this connector are full table; select the option that best fits how you want to refresh the data.
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. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times). Optionally, you can define some additional settings:
  • Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.
  • Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source 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 RD Station Conversas and their corresponding fields. API reference: developers.rdstation.com.
List contacts (GET /v2/customers). Base stream for conversation data; messages_history is a child of this stream.
FieldTypeDescription
_idStringID do contato
full_nameStringNome completo do contato
emailStringEndereço de e-mail do contato
cel_phoneStringNúmero de telefone celular do contato
Address (object):
FieldTypeDescription
address.cityStringCidade
address.complementStringComplemento
address.countryStringPaís
address.districtStringBairro
address.numberStringNúmero
address.stateStringEstado/UF
address.streetStringLogradouro
address.zip_codeStringCEP
Job (object):
FieldTypeDescription
job.cnpjStringCNPJ da empresa
job.companyStringNome da empresa
job.departmentStringDepartamento
job.emailStringE-mail profissional
job.occupation_areaStringÁrea de atuação
job.phoneStringTelefone profissional
job.siteStringSite da empresa
job.titleStringCargo
List custom fields (GET /v2/custom-fields). Variables that can be used in message templates.
FieldTypeDescription
idStringCustom field ID
keyStringVariable to reference in message templates
labelStringLabel of the custom field
infoStringAdditional information about the field
List employees (GET /v2/employees).
FieldTypeDescription
idStringEmployee ID
nameStringEmployee name
emailStringEmployee email address
List flows (GET /v2/flows).
FieldTypeDescription
idStringFlow ID
titleStringFlow title
List message history per contact (GET /v2/messages/history). Child stream of Contacts — one partition per contact. Requires Start Date in the source configuration. Response is encrypted (JWE); use Private Key (JWK) to store decrypted message JSON in the data field; otherwise data contains the encrypted payload.
This stream is available only for the Advanced plan of RD Station Conversas. Basic and Pro plans do not have access to the conversation history API. See planos e preços for details.
FieldTypeDescription
customer_idStringContact ID this message history belongs to
dataStringMessage content: decrypted JSON string if private key is set, otherwise encrypted JWE string
List reports (GET /v4/reports). Uses the Conversas v4 API base.
FieldTypeDescription
idIntegerReport ID
titleStringReport title
descriptionStringReport description
createdAtStringCreation date
updatedAtStringLast update date
List message templates (GET /v2/template/all).
FieldTypeDescription
idStringTemplate ID
titleStringTemplate title
channelStringChannel (e.g. whatsapp, email)
contentStringTemplate text content
content_mediaStringMedia type of the message content
List wallets (GET /v2/wallets).
FieldTypeDescription
idStringWallet ID
nameStringWallet name
List official WhatsApp integrations (GET /v2/whatsapp/integrations/official).
FieldTypeDescription
keyStringOfficial integration key
labelStringIntegration label
List workflows (GET /v2/workflows).
FieldTypeDescription
titleStringWorkflow title
stagesStringWorkflow stages as JSON array string

Data Model

The following diagram illustrates the main relationships. Contacts is the core entity; messages_history is partitioned by contact (child stream). Other streams are independent configuration or metadata entities.

Implementation Notes

Message history and encryption

  • The messages_history stream returns responses encrypted with JWE (RSA-OAEP-256). To store decrypted message content in the data field, configure Private key (JWK) in the source. If not set, the raw encrypted payload is stored in data.
  • Start Date is required for messages_history so the API can filter messages from that date onward (YYYY-MM-DD or common date formats).

Child stream behavior

  • messages_history is a child of contacts. The tap first syncs all contacts, then requests message history for each contact. Selecting both streams will result in one messages history partition per contact; ensure Start Date is set for consistent results.

Skills for agents

Download RD Station Conversas skills file

RD Station Conversas connector documentation as plain markdown, for use in AI agent contexts.