DID reputation monitoring API: see exactly where your numbers are flagged
A DID reputation monitoring API, also called a phone number reputation API, that checks each number against 12 reputation sources in one call and returns which ones flagged it. You know exactly who to contact for remediation before answer rates drop.
{
"phone": "+18005551234",
"spam": {
"callerapi": {
"is_spam": true,
"complaints_count": 12,
"last_complaint_on": "2026-09-14T08:12:00Z"
},
// one key per source that flagged the number,
// each with its own dates and codes.
// A clean source has no key.
}
}
12
reputation sources checked per number, in one API call.
1
answer per source, so you know exactly where to file remediation.
$25
per month to start, on the same plans as the Caller ID API.
"Spam Likely" has many authors. Now you know which one.
A number gets labeled, answer rates fall, and the team starts guessing. Was it a carrier analytics engine, a consumer blocking app, an industry do-not-originate list, a complaint database? Each has its own remediation form. Filing with the wrong one wastes a week.
One call returns the verdict from every source we aggregate. If two of twelve flagged the number, you see which two and you file with those two. Nothing else on the market does this natively, from an API, across this many sources.
+1 800 555 1234
2 of 12 flaggedSources span carrier analytics engines, consumer call-blocking apps, industry do-not-originate lists and our own complaint database. We do not publish the list, and you do not need it: the response names the ones that matter.
Three manual steps become one request
Most teams learn a number is burned when connect rates collapse. Then they search each source by hand. Then they guess where to file.
| Step | Without monitoring | With the API |
|---|---|---|
| Learn a number is flagged | After answer rates drop, days later | Daily job, same day |
| Find where it is flagged | Search each source by hand | In the response, per source |
| File remediation | Guess, wait, repeat | Exact source, first time |
| Whole inventory | Spot checks when someone complains | Every number, every day |
Built for teams that own number inventory
Anyone who hands numbers to customers, or dials from them, needs to know when one turns bad.
CPaaS, UCaaS and wholesale carriers
Put number reputation in your own dashboard as a paid feature. Your customers see where each of their numbers stands, fix the flagged ones before campaigns suffer, and pay you for the visibility. You are the provider. We are the source behind it, and we stay invisible.
This is the most common deployment. Almost every partner resells it.
VoIP providers and resellers
Scan the inventory before you assign a DID. A number that arrives already flagged becomes a support ticket in a week. Now it gets quarantined and remediated first.
Contact centers and dialer teams
Monitor every outbound number daily, rotate the flagged ones, and file remediation with the exact source. Answer rates stop collapsing without warning.
Checking one number by hand?
Use the free caller ID test. The GoHighLevel marketplace app ships the same check inside GHL. When you have more numbers than patience, come back to the API.
The monitoring loop, from code
One GET per number per check. Your scheduler, your thresholds, your remediation queue.
Your inventory
Every DID you own or assign, in +E.164.
Daily check
GET /api/did-reputation/{phone} for each number. 12 sources, one response.
Route the flagged
Pull the number from rotation. Open a remediation case with each source that flagged it.
Back to the pool
When the next check comes back clean on every source, the number goes back to work.
$ for did in $(cat inventory.txt); do
curl -sH "x-auth: $API_KEY" \
"https://callerapi.com/api/did-reputation/$did" \
| jq -r '[.data.phone, (.data.spam | keys | join(","))] | @tsv'
done
+18005551234 callerapi,...
+18005550100 (clean)
DID reputation monitoring API questions
Know before your answer rate does
Grab a key and check your first number in minutes. Managing thousands of DIDs? We will scope a volume plan.