gmail.com, yahoo.com, hotmail.com, outlook.com, aol.com, icloud.com, me.com,
live.com, protonmail.com, proton.me, msn.com, ymail.com, comcast.net, att.net,
verizon.net, mac.com, fastmail.com, hey.com, pm.me, zoho.com, gmx.com,
googlemail.com

.edu, .ac.uk, .ac.jp, .ac.kr, .ac.in, .ac.nz, .ac.za

import re

def extract_name_parts(email):
    local = email.split("@")[0]
    parts = re.split(r'[._\-]', local)
    parts = [p for p in parts if not p.isdigit()]
    parts = [p.capitalize() for p in parts if len(p) >= 2]
    return parts

---

crustdata_company_identify:
  company_website: "domain.com"

crustdata_company_identify:
  company_website: "acme.com"

crustdata_people_enrich:
  business_email: "john@acme.com"
  fields: "name,business_email"

crustdata_people_enrich:
  business_email: "stephen@spero.vc"
  fields: "name,business_email"

crustdata_people_enrich:
  personal_email: "bert.zacharin@gmail.com"
  enrich_realtime: true

crustdata_people_enrich:
  personal_email: "joanne.bradford@gmail.com"
  enrich_realtime: true

def verify_employer_domain(profile, email_domain):
    domain_base = email_domain.lower().split('.')[0]
    for emp in profile.get("current_employers", []) + profile.get("past_employers", []):
        for d in emp.get("employer_company_website_domain", []):
            if email_domain.lower() in d.lower() or d.lower() in email_domain.lower():
                return True, emp.get("employer_name", "")
        if len(domain_base) > 3 and domain_base in emp.get("employer_name", "").lower().replace(" ", ""):
            return True, emp.get("employer_name", "")
    return False, None

def name_matches_prefix(profile_name, email_prefix):
    pn_parts = profile_name.lower().split()
    prefix = email_prefix.lower()
    for part in pn_parts:
        if prefix.startswith(part[:3]) or part.startswith(prefix[:3]):
            return True
        # First-initial + lastname pattern: "talling" = "t" + "alling"
        if len(prefix) > 2:
            for i in range(1, min(3, len(prefix))):
                if prefix[i:] in part and len(prefix[i:]) > 2:
                    return True
    return False

crustdata_web_search:
  query: "who is talling@lamppostgroup.com"
  sources: ["ai"]

crustdata_people_search_db:
  filters:
    op: "and"
    conditions:
      - filter_type: "name"
        type: "(.)"
        value: "FirstName"
      - filter_type: "current_employers.name"
        type: "(.)"
        value: "CompanyName"
  page_size: 3

def verify_name_match(email_name_parts, profile_name):
    if not email_name_parts or not profile_name:
        return False
    return email_name_parts[0].lower() in profile_name.lower()

undefined

Check each returned profile: does "kyle" appear in the profile's name? If yes, it's a match.

crustdata_people_search_db:
  filters:
    op: "and"
    conditions:
      - column: "emails"
        type: "(.)"
        value: "LOCAL_PART_OF_EMAIL"
  page_size: 5

undefined

undefined

def verify_phase4_match(email, name_parts, profile, domain_map):
    profile_name = profile.get("name", "").lower()

    # Name verification
    if len(name_parts) >= 2:
        if not (name_parts[0].lower() in profile_name and name_parts[-1].lower() in profile_name):
            return False
    elif len(name_parts) == 1 and len(name_parts[0]) > 2:
        if name_parts[0].lower() not in profile_name:
            return False
    else:
        return False

    # Org verification for work/edu
    domain = email.split("@")[1]
    company_info = domain_map.get(domain)
    if company_info:
        org_name = company_info.get("name", "")
        skip = {"the", "inc", "llc", "ltd", "co", "corp", "of", "and", "for", "university", "college"}
        org_words = [w.lower() for w in org_name.split() if w.lower() not in skip and len(w) > 2]
        profile_str = str(profile).lower()
        if org_words and not any(w in profile_str for w in org_words):
            return False

    return True

crustdata_people_search_db:
  filters:
    op: "and"
    conditions:
      - filter_type: "name"
        type: "(.)"
        value: "FirstName LastName"
  page_size: 5

undefined

If 1-3 results returned, take the first one. If 0 or 4+, mark as unmatched.

crustdata_web_search:
  query: "EMAIL linkedin"
  sources: ["web"]

crustdata_web_search:
  query: "who is EMAIL"
  sources: ["ai"]

crustdata_people_search_db:
  filters:
    op: "and"
    conditions:
      - filter_type: "name"
        type: "(.)"
        value: "Extracted Name"
  page_size: 3

crustdata_people_enrich:
  linkedin_profile_url: "PROFILE_URL_FROM_STEP_1_OR_2"
  fields: "name,business_email"

{
  "phase_completed": 3,
  "domain_map": {
    "acme.com": {"name": "Acme Corp"},
    "stanford.edu": {"name": "Stanford University"}
  },
  "results": {
    "john@acme.com": {
      "name": "John Smith",
      "headline": "VP Engineering at Acme",
      "company": "Acme Corp",
      "method": "person_enrich"
    }
  },
  "unmatched_emails": ["unknown@gmail.com"]
}

=== Email Enrichment Results ===
Total emails: {N}
  Work:     {W}  | Person: {P1} ({P1%})  | Company: {C1} ({C1%})
  Edu:      {E}  | Person: {P2} ({P2%})  | Company: {C2} ({C2%})
  Personal: {R}  | Person: {P3} ({P3%})  | Company: {C3} ({C3%})
  Overall:  {N}  | Person: {PT} ({PT%})  | Company: {CT} ({CT%})

Breakdown by method:
  Phase 2 (person_enrich):    {count}
  Phase 3 (name+company):     {count}
  Phase 4 (email_contains):   {count}
  Phase 5 (name_search):      {count}

For each email:
|
+-- Classify: work / edu / personal
|
+-- Phase 1: Is it work or edu?
|   +-- Yes -> Extract domain -> crustdata_company_identify(company_website=domain)
|   |   +-- Found company? -> Store in domain_map
|   |   +-- Not found? -> Continue (no company info for this domain)
|   +-- No (personal) -> Skip to Phase 2 Branch B
|
+-- Phase 2: Branch by email type
|   |
|   +-- Work/edu (Branch A):
|   |   +-- crustdata_people_enrich(business_email=email, fields="name,business_email")
|   |   +-- Found person? -> Post-verify (employer domain + name prefix + AI correction)
|   |   |   +-- Verified? -> DONE (method=person_enrich)
|   |   |   +-- Failed verification? -> Continue to Phase 3
|   |   +-- Not found? -> Continue to Phase 3
|   |
|   +-- Personal (Branch B):
|       +-- crustdata_people_enrich(personal_email=email, enrich_realtime=true)
|       +-- Found person? -> DONE (method=person_enrich_personal) -- no post-verification needed
|       +-- Not found? -> Continue to Phase 4 (skip Phase 3)
|
+-- Phase 3: Is it work/edu AND have company name AND name parts?
|   +-- Yes -> crustdata_people_search_db(filters: name + current_employers.name)
|   |   +-- Found + name verified? -> Phase 7 scoring gate -> DONE (method=name+company)
|   |   +-- Not found? -> Continue to Phase 4
|   +-- No -> Skip to Phase 4
|
+-- Phase 4: Still unmatched? (any email type)
|   +-- crustdata_people_search_db(filters: column="emails", type="(.)", value=local_part)
|   +-- For each result, verify:
|   |   +-- Name parts match profile name? (required)
|   |   +-- Work/edu: org appears in profile history? (required)
|   |   +-- Personal: name match only (no org check possible)
|   +-- Verified match? -> Phase 7 scoring gate -> DONE (method=email_contains)
|   +-- No verified match? -> Continue to Phase 5
|
+-- Phase 5: Is it personal AND has 2+ name parts?
|   +-- Yes -> crustdata_people_search_db(filters: name="FirstName LastName")
|   |   +-- 1-3 results returned + name verified? -> Phase 7 scoring gate -> DONE (method=name_search)
|   |   +-- 0 or 4+ results? -> Continue to Phase 6
|   +-- No -> Continue to Phase 6
|
+-- Phase 6: Still unmatched? (any email type)
|   +-- crustdata_web_search(query="EMAIL linkedin", sources=["web"])
|   |   +-- Found linkedin.com/in/ URL? -> crustdata_people_enrich(linkedin_profile_url=URL) -> Phase 7 scoring gate -> DONE
|   +-- No URL found? -> crustdata_web_search(query="who is EMAIL", sources=["ai"])
|   |   +-- Extracted person name? -> crustdata_people_search_db(name) -> get profile URL -> enrich -> Phase 7 scoring gate -> DONE
|   +-- Nothing found? -> UNMATCHED
|
+-- Phase 7: Scoring gate (applied to all candidates from Phases 3-6)
    +-- Requires BOTH: name_sim > 0.8 AND combined_score > 0.7
    +-- Pass? -> Accept match
    +-- Fail? -> Reject, continue to next phase or mark UNMATCHED

crustdata_people_search_db:
  filters:
    op: "and"
    conditions:
      - filter_type: "name"
        type: "(.)"
        value: "Person Name"
      - filter_type: "current_employers.name"
        type: "(.)"
        value: "Company Name"
  page_size: 3

crustdata_web_search:
  query: "Person Name Company site:linkedin.com/in/"

crustdata_people_enrich:
  linkedin_profile_url: "https://linkedin.com/in/person1,https://linkedin.com/in/person2,..."
  fields: "name,business_email"

crustdata_people_enrich:
  linkedin_profile_url: "https://linkedin.com/in/person1,https://linkedin.com/in/person2,..."
  fields: "personal_contact_info.personal_emails,personal_contact_info.phone_numbers"

crustdata_people_enrich:
  linkedin_profile_url: "https://linkedin.com/in/person1"
  fields: "name,business_email,personal_contact_info.personal_emails,personal_contact_info.phone_numbers"

crustdata_people_enrich:
  linkedin_profile_url: "https://linkedin.com/in/person1"
  fields: "github_profiles"

crustdata_web_search:
  query: "Person Name Company site:github.com"

crustdata_web_fetch:
  url: "https://api.github.com/users/USERNAME/repos?sort=created&direction=asc&per_page=5"

crustdata_web_fetch:
  url: "https://github.com/OWNER/REPO/commit/SHA.patch"