Insurance AI Automation
Fiber AI email-to-person endpoint example
7 min read
Sales agents and recruiting workflows die on bad data. The email-to-person endpoint is how Fiber AI turns a single email address—work or personal—into a complete, verified identity your systems and AI agents can actually use.
This guide walks through exactly how the Fiber AI email-to-person endpoint works, when to use it, and a concrete example you can drop into your stack today.
The Quick Overview
- What It Is: A live API endpoint that takes any email (work or personal) and returns a full person profile with verified contact details.
- Who It Is For: Growth, sales, marketing, and recruiting teams, plus AI agent builders who need to resolve anonymous emails into real B2B identities at scale.
- Core Problem Solved: You get inbound signups, CSVs, or legacy CRM records with half-broken emails and no context—this endpoint turns those into complete, verified profiles with <1% bounce rates.
How It Works
At its core, Fiber AI’s email-to-person endpoint does one thing very well: given an email, it finds the right person across 850M+ professionals, verifies the contact using a multi-step waterfall, and returns a usable identity object in real time.
Under the hood, the flow looks like this:
-
Identity Resolution:
Fiber maps the email (work or personal) to an individual using its people graph, historical work history, and live sources like LinkedIn. -
Waterfall Validation & Bounce Detection:
The email is checked through four layers of validation (SMTP checks, pattern checks, historical bounce data, proprietary scoring) to ensure you only get contacts that will actually deliver. -
Profile & Context Enrichment:
Once the person is resolved and the email is validated, Fiber enriches the profile with LinkedIn data, job title, company, location, and other fields your sales or recruiting workflows depend on.
You only pay credits for successful calls where Fiber returns data, not for empty or failed lookups.
Basic email-to-person example (single lookup)
Here’s the simplest way to use the endpoint: resolve a single email into a profile.
Request example
curl https://api.fiber.ai/v1/email-to-person/single \
--request POST \
--header 'Content-Type: application/json' \
--data '{
"apiKey": "YOUR_API_KEY",
"email": "john@company.com"
}'
Sample response (truncated for clarity)
{
"data": [
{
"first_name": "John",
"last_name": "Smith",
"name": "John Smith",
"headline": "Software Engineer at Tech Corp",
"locality": "San Francisco, CA",
"profile_pic": "https://media.licdn.com/dms/image/...",
"linkedin_url": "https://www.linkedin.com/in/john-smith-123456/",
"title": "Senior Software Engineer",
"company": "Tech Corp",
"company_domain": "techcorp.com",
"work_email": "john@techcorp.com",
"personal_email": "johnsmith@gmail.com",
"verified": true,
"confidence": 0.98,
"bounce_risk": "low"
}
],
"meta": {
"success": true,
"credits_used": 1,
"source": "waterfall_verified"
}
}
What you get from a single input email:
- Full name and LinkedIn profile
- Current title, company, and company domain
- Work email (and sometimes personal email and phone)
- Verification flags (verified, confidence score, bounce risk)
This is the backbone for “who is this lead?” and “is this email safe to send to?” inside your outbound or lifecycle flows.
Features & Benefits Breakdown
| Core Feature | What It Does | Primary Benefit |
|---|---|---|
| Work & personal email resolution | Maps a work or personal email to a real person profile. | Turns anonymous signups / old CRM records into usable leads. |
| Waterfall validation & bounce checks | Runs four layers of validation before returning an email as usable. | Protects sender reputation with <1% bounce rates and 0% Bounce Guarantee. |
| Deep profile enrichment | Returns LinkedIn, title, company, location, and more. | Lets AI agents and sales teams prioritize and route by ICP. |
Ideal Use Cases
-
Best for inbound signup enrichment:
Because it can take agmail.comsignup, resolve the person, and attach their work identity + company so you can qualify them properly. -
Best for CRM clean-up & revival:
Because it can scan legacy CRM emails, verify them, and return current job, company, and deliverable contacts to safely re-engage dormant lists.
Real-world workflows with examples
1. Enriching inbound signups from personal emails
Problem: Your signup form gets johnsmith@gmail.com with a first name and nothing else. Your SDRs have no idea if this is a founder at a $50M ARR company or a student testing your product.
With email-to-person, you can automatically resolve and qualify this in your backend:
Pseudo-code example (Node.js-style)
import fetch from "node-fetch";
async function enrichSignup(email) {
const res = await fetch("https://api.fiber.ai/v1/email-to-person/single", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
apiKey: process.env.FIBER_API_KEY,
email
})
});
const { data } = await res.json();
const person = data?.[0];
if (!person) return null;
return {
email,
firstName: person.first_name,
lastName: person.last_name,
title: person.title,
company: person.company,
companyDomain: person.company_domain,
linkedin: person.linkedin_url,
verified: person.verified,
bounceRisk: person.bounce_risk
};
}
You can then:
- Auto-route high-intent signups (e.g., “VP Engineering at Series B SaaS”) to SDRs.
- Push verified emails and company data into your CRM or MAP.
- Trigger different onboarding flows based on title/company size.
2. Cleaning and upgrading old CRM records
Problem: Your CRM is full of stale records like jane@oldstartup.com—company was acquired, domain changed, and your emails bounce.
With email-to-person, you can:
- Resolve
jane@oldstartup.comto Jane’s current identity. - Get her current company, verified work email, and LinkedIn.
- Only send campaigns to records that pass Fiber’s waterfall validation.
Bulk clean-up pattern (pseudo-code)
def clean_crm_emails(emails):
cleaned = []
for email in emails:
resp = requests.post(
"https://api.fiber.ai/v1/email-to-person/single",
json={"apiKey": FIBER_API_KEY, "email": email}
).json()
person = (resp.get("data") or [None])[0]
if not person or not person.get("verified"):
continue # skip risky / unresolved records
cleaned.append({
"original_email": email,
"clean_email": person.get("work_email") or email,
"name": person.get("name"),
"title": person.get("title"),
"company": person.get("company"),
"linkedin": person.get("linkedin_url"),
"bounce_risk": person.get("bounce_risk")
})
return cleaned
Outcome: safer reactivation campaigns, better personalization, and significantly fewer bounces.
Limitations & Considerations
-
Coverage is strongest on B2B / professional identities:
Fiber focuses on 850M+ professionals and 40M+ companies. Purely personal or non-professional personas (no work history, no LinkedIn trace) may not resolve. -
API-key and rate limit management:
High-volume users should plan for appropriate rate limits and batching. Fiber provides higher limits and dedicated Slack support on enterprise plans.
Pricing & Plans
Fiber AI uses a credit-based, success-driven pricing model: you only burn credits when Fiber actually finds data for your query.
Typical patterns:
- Credits are consumed per successful email-to-person lookup.
- “Not found” or failed resolutions do not consume credits.
- Volume discounts and custom endpoint work are available for teams replacing ZoomInfo, Apollo, or People Data Labs across their stack.
Example packaging:
- Growth Plan: Best for GTM and data teams needing reliable enrichment for tens to low hundreds of thousands of contacts per month, plus standard rate limits and support.
- Enterprise / Platform Plan: Best for AI agent platforms, large RevOps teams, and infrastructure providers needing millions of lookups, higher rate limits, custom endpoints, and Slack-based priority support.
For exact pricing and volume tiers, we walk teams through their current vendor costs and typically deliver 80%+ savings compared to legacy data providers.
Frequently Asked Questions
Can Fiber AI resolve personal emails like Gmail or Yahoo, or only work emails?
Short Answer: Yes, Fiber AI can resolve both work and personal emails into a person profile.
Details:
The email-to-person endpoint is explicitly built to answer, “Who is behind this email?” for both @company.com and @gmail.com-style addresses. For personal emails, Fiber uses its identity graph and live sources (e.g., LinkedIn) to match the email to a professional profile, then returns work details (title, company, location) where available. This is especially powerful for inbound signups and waitlists that skew heavily toward personal emails.
How does Fiber AI keep bounce rates so low for email-to-person results?
Short Answer: Fiber uses a four-layer waterfall validation system and only charges you for contacts it believes are safe.
Details:
When you call the email-to-person endpoint, Fiber doesn’t just pattern-match an email and return it raw. It runs waterfalls that include SMTP checks, proprietary scoring, historical bounce intelligence, and external verifiers. If an email fails these checks, it won’t be returned as a verified, low-risk contact—and you don’t pay a credit. This is how Fiber supports sub-1% bounce rates and offers a 0% Bounce Guarantee at volume, letting you scale outbound without torpedoing your sender reputation.
Summary
Fiber AI’s email-to-person endpoint turns a single email—work or personal—into a fully enriched, verified identity your sales, marketing, recruiting, and AI agents can trust. You get:
- Identity resolution across 850M+ professionals.
- Verified emails with four-layer bounce detection.
- Complete profile context (LinkedIn, title, company, location).
Teams use it to unlock hidden pipeline from personal-email signups, clean and revive old CRMs, and give AI agents a reliable data layer that doesn’t break under real-world volume.