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Odoo is an open-source enterprise resource planning (ERP) system that helps businesses manage their operations, including sales, inventory, accounting, manufacturing, and more. It provides a comprehensive suite of integrated business applications designed to streamline workflows and improve efficiency.

Configuring Odoo as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Odoo 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 authorize Nekt to access your Odoo instance. Provide the necessary credentials and connection details for your Odoo installation. The following configurations are available:
  • API URL: The base URL of your Odoo instance (e.g., https://mycompany.odoo.com). This is the root URL where your Odoo instance is hosted.
  • API Key: The API key (bearer token) to authenticate against the Odoo API. This token grants access to your Odoo instance and must have the necessary permissions to read the data you want to extract.
  • Database: (Optional) The name of the database to connect to. This is only required when a single Odoo server hosts multiple databases. If your instance uses a single database or the database name is determined automatically, you can leave this field empty.
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.
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: 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, for example, 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, for example, 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. 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 Odoo and their corresponding fields:
Stream for retrieving payment records from Odoo’s account.payment model. This stream contains payment transactions and their associated details.
Stream for retrieving insurance quotation records from Odoo’s mut.insurance.quotation model. This stream contains insurance quotation data specific to your Odoo configuration.
Stream for retrieving policy records from Odoo’s mut.policy model. Contains insurance policy data including proponent details, coverage, and payment information.
Stream for retrieving policy certificate records from Odoo’s mut.policy.certificate model. Contains certificate (item) data per policy, including vehicle and coverage details.
Stream for retrieving certificate coverage records from Odoo’s mut.certificate.coverage model. Contains coverage lines linked to policy certificates.
Stream for retrieving insurance item coverage records from Odoo’s mut.insurance.item.coverage model.
Stream for retrieving policy extra product records from Odoo’s mut.policy.extra.product model.

Data Model

The following diagram illustrates the relationships between the data streams in Odoo. Each stream represents a distinct Odoo model and operates independently.

Use Cases for Data Analysis

This guide outlines valuable business intelligence use cases when consolidating Odoo data, along with ready-to-use SQL queries that you can run on Explorer.

1. Payment Analysis Overview

Track payment transactions, analyze payment patterns, and monitor financial flows from your Odoo system. Business Value:
  • Monitor payment transactions and cash flow
  • Analyze payment methods and patterns
  • Track outstanding payments and reconciliation status
  • Generate financial reports based on payment data

2. Insurance Quotation Tracking

Analyze insurance quotation trends, conversion rates, and customer behavior patterns. Business Value:
  • Track quotation creation and conversion rates
  • Identify trends in quotation volume over time
  • Analyze customer segments and quotation performance
  • Monitor quotation status and workflow progression

Implementation Notes

Dynamic Schema Discovery

  • The Odoo connector uses dynamic schema discovery by calling the fields_get method on each Odoo model
  • This means the exact fields available may vary based on:
    • Your Odoo version
    • Installed modules and apps
    • Custom fields and configurations
    • Model-specific customizations
  • If schema discovery fails, the connector falls back to a basic schema with only the id field

Data Quality Considerations

  • Odoo model fields may include relationships (many2one, one2many, many2many) that are represented as integer IDs or arrays
  • Date and datetime fields are automatically converted to appropriate types
  • Monetary fields are handled as numeric types
  • Binary fields are represented as strings
  • Fields defined as string in the stream schema (e.g. vehicle_cc) are coerced from numeric values (e.g. 0) to string when the API returns numbers, so targets receive schema-compliant types

API Limits & Performance

  • The connector uses pagination with a default page size to efficiently extract large datasets
  • For faster extractions, select only the streams necessary for your analysis
  • Odoo API rate limits may apply depending on your instance configuration
  • Ensure your API key has appropriate read permissions for the models you want to extract

Multi-Database Support

  • If your Odoo instance hosts multiple databases, specify the database name in the configuration
  • The database name is sent as the X-Odoo-Database header in API requests
  • Leave the database field empty if your instance uses a single database or auto-detection

Skills for agents

Download Odoo skills file

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