Use AI to validate and enhance new Brevo contacts

Questions
,
1

:bullseye: What is your goal?

I use Brevo for my CRM and email marketing. When I meet new people at events, I often only get a name and email. I would like to design an automation that is triggered when I enter that limited contact information into Brevo. The trigger then sends that information to an AI tool (I use Gemini primarily) to research additional contact information for that person, validates that information, and then adds that information to the Brevo contact details.

:thinking: What is the problem & what have you tried?

I can’t figure out how to get Gemini to communicate with Brevo to append the conact record.

1 Like
3

Hey Jospeh,

in essence, have your AI tool return the data in a predefined JSON and use that to fill in the Update a Contact Brevo module.

1 Like
4

If you are iPhone user you can utilize Siri Shortucts and create simple trigger workflow.

The moment you put name+email+comments it sends data to Make.com using webhook and Make.com handles rest- adds contact to Brevo, triggers Gemini and after research is done- adds additional informations to Brevo.

Very nice project- start with mapping your ideal process- which steps should be taken and what should happen on each of them and then start building automation.

PS. I don’t know any alternative for Siri Shortcuts for Android- you can use free forms builders like Tally.so

Have a nice day,
Michal

5

Hey Joseph, I agree with the Make → AI → Brevo approach, but the tricky part is getting reliable contact enrichment from the AI step.

I work on a tool with agent tasks specifically built for this: given a name and email, research the person’s company, title, LinkedIn, and other details. The agents are tuned for web research and cross-reference multiple sources before returning data.

You can call it via the SDK (https://github.com/futuresearch/everyrow-sdk) or integrate it into Make as a custom HTTP module. The output is structured JSON you can map directly to your Brevo contact fields.

Example for a single contact:

from everyrow.ops import single_agent

result = await single_agent(
    task="Find this person's company, job title, and LinkedIn profile",
    input={"name": "John Smith", "email": "john@example.com"},
)

Happy to help if you want to talk through the Make integration.