Check addresses at sign-up or before a campaign, so you only send to mailboxes that exist.
AI risk scoring ranks addresses by likely harm, beyond pass or fail.
{
"address": "user@example.com",
"verdict": "deliverable",
"checks": {
"syntax": "pass",
"domain": "pass",
"mailbox": "unknown",
"disposable": false,
"role_account": false
}
}
Catch malformed addresses and domains that cannot receive mail.
Flag throwaway addresses that never engage.
Spot addresses like info@ and support@ before you mail them.
Offer a fix for common mistakes at the sign-up form.
Upload a list or validate one address at a time.
Undeliverable results feed your suppression list.
Validate in bulk before a campaign or live at sign-up.
Every address gets a result and the reason behind it.
Remove or fix the rest before they become bounces.
Switch between stages to see what you control at each step. Illustrative interface with sample data.
High bounce rates are the fastest way to lose inbox placement. Validation keeps them low.
Upload a CSV, review verdicts and remove undeliverable addresses before sending. Bounces from a stale list are avoidable, and a clean send protects the reputation you built.
Call the validation API as someone submits your form. Reject malformed addresses, suggest typo fixes, and block disposable domains before they enter your database. Fewer junk records reach your database.
Before mailing contacts you have not emailed in a long time, validate them. Addresses that no longer exist are removed so a win-back campaign does not spike bounces.
Flag info@ and support@ style addresses in imported lead lists. You can route them differently or exclude them, since they often have higher complaint and lower engagement rates.
Beyond pass or fail, a risk score ranks each address by how likely it is to bounce or complain, using domain patterns and history. You set the cutoff and decide what is removed.
A language model proposes the most likely intended address for misspellings, including less common domains. At sign-up, the visitor confirms the suggestion; nothing is changed silently.
After a bulk run, the copilot summarises what it found, such as patterns in disposable domains, and recommends next steps. You review the summary before deleting any contacts.
Unusual surges of invalid or disposable sign-ups often signal bot attacks. Anomaly detection flags them so your team can add friction to the form. Blocking remains your choice.
AI features are assistive: scores and suggestions inform your decisions, and you control what is removed or blocked. [Confirm which AI features are available at launch.]
Stopping a bad address at sign-up is cheaper than cleaning it later. Combine a real-time check with a clear typo prompt on the form.
Treat unknown results as risky. Send them in a small, separate batch and watch bounces before deciding whether to include them in larger sends.
Addresses decay as people change jobs and close accounts. Re-check lists before large sends, especially ones that have been idle for months.
Validation confirms an address can receive mail, not that its owner wants it. Confirmation emails verify consent and catch typos that pass syntax checks.
Feed undeliverable results into your suppression list so removed addresses are never re-imported by a later upload or integration.
Email validation checks whether an address is correctly formatted, uses a domain that can receive mail, and shows signs of a real mailbox. It also flags risky types such as disposable and role addresses, so you can avoid sending to addresses that will bounce.
Upload your list for bulk validation, review the verdict and reason for each address, then export the deliverable ones as CSV. Fix obvious typos and remove undeliverable addresses before your campaign. Send risky or unknown addresses cautiously, in small batches.
No. Some providers do not reveal whether a mailbox exists, so those results are marked unknown rather than guessed. Validation greatly reduces bounces but cannot remove every risk. Monitor bounce rates after sending. Checks that do contact a mail server can still be inconclusive, which is why some results come back as unknown.
[Confirm how mailbox checks are performed.] Syntax, domain and disposable checks do not involve contacting the recipient. Check the documentation for details on mailbox-level signals. Mailbox-level checks vary by provider, and some servers accept all recipients, so even a passing result is never an absolute guarantee of delivery to a person.
[Describe credit counting and expiry.] Validation is a credit add-on, so you pay for checks you use. See the pricing page for current credit packs. [price] Expect credits to be consumed per address checked, whether bulk or single, with details of expiry to be confirmed before launch of this add-on.
A disposable address comes from a throwaway service and usually stops working soon. A role address, such as info@ or support@, goes to a team rather than a person. Both are legitimate technically, but often engage poorly, so we flag them separately.
AI risk scoring ranks addresses by likelihood of bouncing, suggests corrections for typos and summarises list problems in plain language. These are recommendations only, and you decide what to remove. [Confirm which AI features are available at launch.] Treat all scores as guidance only.
Yes, the free email validator tool checks one address at a time so you can try it before using bulk or API validation. Use it to see which checks run and how verdicts are shown. Bulk and API options help at scale.
Some providers do not reveal mailbox status, so those results are marked unknown rather than guessed.
Create an account, add your domain and send your first email.