Turn chat introductions into structured names
Get a clean first name, surname, gender signal, and grammatical cases from every introduction.
Trigger
New WhatsApp Message Received
Polling trigger that monitors for new messages received in TimelinesAI WhatsApp chats.
Action
Clean Name (FIO)
Tool to standardize and parse full names (fio), detect gender, and return grammatical cases. use when you need structured name parsing and declensions from raw fio inputs.
Why this helps
Names in chats often mix nicknames, initials, and different word orders.
- Separate surname, given name, and patronymic
- Support personalized replies
- Reduce ambiguity in contact records
Setup
Build it in a few focused steps.
- 1Connect TimelinesAI and Dadata ru in Notis.
- 2Create an automation telling Notis to identify likely full names in each new message and clean them.
- 3Choose New WhatsApp Message Received as the trigger.
- 4Select a report destination and test with an introduction message.
Questions about this workflow
Will it mistake ordinary words for names?
Ask Notis to return confidence or flag ambiguous text for review.
Can I use the grammatical cases?
Yes, the action returns declensions that can support personalized Russian messages.
When this happens · Trigger
Do this · Action
Supported Triggers and Actions
Notis builds workflows that link Timelinesai to Dadata ru. A trigger fires from one place; an action lands in another.
Timelinesai triggers
Dadata ru actions
Recurring trigger
Notis starts this workflow on a schedule, such as daily, weekly, or during business hours.
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Connect any two apps with Notis in the middle.
Timelinesai and Dadata ru, or any other combination from 1,000+ integrations.
When this happens · Trigger
Do this · Action
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No card. Works with personal or business Dadata ru.