The gap in agent-driven data pipelines
Agents handling leads, signups, or outreach lists will happily write garbage into a CRM, because nothing stops them. A disposable address burns a follow-up email. A typo'd domain bounces and quietly damages sender reputation. A role-based inbox like info@ gets treated like a real contact and skews every report downstream. None of this looks like a failure to the agent — the write succeeded, the task is "done." The bad data just sits there until someone notices months later.
Verify email before the write, not after
The pattern is simple: verify before the write happens, not as a cleanup pass afterward. Your agent calls Tickstem's verify endpoint with the address it's about to use, gets an answer back immediately, and only proceeds to write a contact — to a CRM, a mailing list, anywhere — once it knows the address is actually worth keeping.
What AI agent email verification actually catches
Syntax
Malformed addresses rejected before anything else is checked — the cheapest, fastest filter.
MX records
Confirms the domain actually has mail exchange records — catches typo'd and fake domains that look plausible but can't receive mail.
Disposable domains
Known throwaway email providers flagged and blocked by default — the signups least likely to ever engage again.
Role-based inboxes
Generic addresses like info@, admin@, noreply@ flagged for review instead of treated as a real person.
Calling it from agent code
curl -X POST https://api.tickstem.dev/v1/verify \
-H "Authorization: Bearer $TICKSTEM_API_KEY" \
-d '{"email": "[email protected]"}'
# Response
{
"valid": true,
"mx_found": true,
"disposable": false,
"role_based": false,
"reason": ""
}
A disposable address comes back with "valid": false and "disposable": true, so your agent can block the write outright. A role-based address comes back "valid": true with "role_based": true — still technically deliverable, but worth routing to a human review step rather than treating it like a confirmed real contact.
Using it from Melaya
Before a Melaya agent writes a new contact to a connected CRM like HubSpot, it calls Tickstem verify first. Invalid syntax, missing MX records, and disposable domains block the write before it happens; role-based addresses get routed to a review step instead of an automatic accept or reject. This fits the same governance pattern Melaya already uses for consequential writes — verification is a fast, automatic read, and only a flagged result needs a human to look at it.
Getting started
Create a free account at tickstem.dev and generate an API key. The free tier includes 500 verifications a month, no credit card required.
Frequently asked questions
How do I stop an AI agent from writing bad data to my CRM?
Verify each email address with Tickstem before the agent writes the contact, not after. A single API call checks syntax, MX records, disposable domains, and role-based prefixes, and returns an instant valid-or-not answer your agent's code can act on before the write happens.
What does AI agent email verification actually catch?
Invalid syntax, missing MX records (the domain doesn't accept mail at all), known disposable email providers, and role-based inboxes like info@ or admin@ that are unlikely to belong to a real contact.
Does email verification contact the recipient's mail server?
No. Verification never performs an SMTP probe against the destination mail server. It's fast, doesn't affect your sender reputation, and doesn't alert the recipient's mail provider.
Should role-based email addresses be auto-rejected?
Not necessarily. Addresses like info@ or support@ aren't always wrong — they can belong to a real team inbox. Route them to a review step instead of an automatic reject, and let a human make the call.
Keep bad data out of your CRM
Email verification for agent-driven pipelines — syntax, MX records, disposable domains, and role-based inboxes, one API call. 500 free verifications a month, no credit card required.
Start for free →Related: Email verification → · Tickstem × Melaya partner page · Tickstem + Melaya: infrastructure for AI agents