Turn raw vehicle details into structured fields
Send vehicle information as captured and let Dadata ru extract the useful identifiers for the paperwork that follows.
Trigger
Webhook received
Notis starts this workflow when an external tool or custom backend sends an HTTP request.
Action
Clean Vehicle
Identifies and standardizes a vehicle's make and model from text.
Why this helps
Vehicle information typed in free form takes time to untangle and can leave important identifiers buried in text.
- Extract brand, model, year, VIN, and other identifiers from raw vehicle information.
- Reduce manual parsing before paperwork preparation.
- Keep vehicle details structured for review and reuse.
Setup
Build it in a few focused steps.
- 1Connect ActiveMerge and Dadata ru once in the Notis portal.
- 2Create an automation in Automations, New Automation, and name it for vehicle detail parsing.
- 3Tell Notis to parse the submitted raw vehicle information with Dadata ru and return the structured fields.
- 4Choose the webhook trigger and select a report destination.
- 5Test with one real vehicle information example.
Questions about this workflow
Which fields can be extracted?
The action description includes brand, model, year, VIN, and other identifiers.
Does it check vehicle ownership?
No ownership check is stated for this action. It standardizes and parses vehicle data.
Does ActiveMerge generate the paperwork?
This package uses the Dadata ru parsing action. No ActiveMerge document action is listed.
When this happens · Trigger
Do this · Action
Supported Triggers and Actions
Notis builds workflows that link ActiveMerge to Dadata ru. A trigger fires from one place; an action lands in another.
ActiveMerge triggers
Dadata ru actions
Recurring trigger
Notis starts this workflow on a schedule, such as daily, weekly, or during business hours.
Clean Address
Standardizes a Russian postal address and parses its components.
Webhook trigger
Notis starts this workflow when an external tool or custom backend sends an HTTP request.
Clean Birthdate
Standardizes birthdates and reports whether they could be parsed.
Clean Email
Cleans and validates an email address, correcting common domain typos.
Clean Name (FIO)
Parses and standardizes a full name, with gender and grammatical forms.
Clean Passport
Checks a Russian passport number against the official registry.
Clean Phone
Standardizes and validates a phone number.
Clean Vehicle
Identifies and standardizes a vehicle's make and model from text.
Clean Composite Record
Standardizes contact records containing multiple types of data.
Connect any two apps with Notis in the middle.
ActiveMerge and Dadata ru, or any other combination from 1,000+ integrations.
When this happens · Trigger
Do this · Action
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