Enrich CRM company records from supplied domains

Quick answer

A company enrichment pilot should map each supplied domain to source-linked fields and an observation time. Keep uncertain parent, subsidiary, or trading-name matches in review, and allow CRM updates only after a human approves accepted rows. The download is synthetic; no managed enrichment service or CRM integration is promised.

{
    "input_domain": "example.com",
    "company_name": "Example Harbor Labs",
    "source_url": "https://example.com/company",
    "observed_at": "2026-09-17T00:00:00Z",
    "field_status": "accepted"
}

Fit company data to a CRM task

Use this workflow when a CRM or RevOps team already has a domain list and needs a reviewable company record before changing customer data. It also suits a builder validating how a domain-to-record pipeline should represent missing or ambiguous values.

The proposed output describes company records, not a ready-made customer database or contact list. The included example contains two synthetic domains and invented organizations. It does not verify either domain or organization.

Define the record contract

A valid URL and timestamp do not prove that a company match is correct. Keep missing values null; do not fill them from a plausible name or nearby organization. If a row is held for review, preserve the reason with it.

Protect CRM and personal data

Keep company fields separate from personal contact records. Do not add email addresses, phone numbers, inferred headcount, or individual profiles to this company schema without a separately defined purpose and permitted use.

Before transferring any personal data, agree the purpose, source, retention period, access, and correction process. Where the EU General Data Protection Regulation applies, Article 5 sets principles including purpose limitation, accuracy, and storage limitation. Applicability depends on the specific parties and processing; this checklist is not a legal determination.

Validate the synthetic JSON

Download the synthetic JSON sample or CSV sample, and use the pilot brief to prepare implementation questions. Save the JSON as sample.json, then save the code below as validate-sample.py beside it. Run the local check with Python 3.12.0; Windows instructions are not included. Install Python from the official downloads page. See the Python JSON documentation for file parsing.

python3 --version
python3 validate-sample.py

The standard-library script routes ambiguous rows to review. It does not update a CRM or call a ProxyLane API. The validator sends malformed URLs and values of the wrong type to review rather than treating them as accepted. It still checks only this synthetic record contract; it does not verify a live source or make a service request.

import json
from datetime import datetime
from pathlib import Path
from urllib.parse import urlsplit

SAMPLE_PATH = Path("sample.json")
ALLOWED_HOSTS = {"example.com", "example.org"}


def is_synthetic_https_url(value):
    if not isinstance(value, str):
        return False
    try:
        parsed_url = urlsplit(value)
        hostname = parsed_url.hostname
        parsed_url.port
        username = parsed_url.username
        password = parsed_url.password
    except ValueError:
        return False
    return (parsed_url.scheme == "https"
            and hostname in ALLOWED_HOSTS
            and username is None
            and password is None)
ALLOWED_STATUSES = {"accepted", "review", "unknown"}
REQUIRED_FIELDS = {
    "input_domain",
    "company_name",
    "source_url",
    "observed_at",
    "field_status",
}

sample = json.loads(SAMPLE_PATH.read_text(encoding="utf-8"))
if sample.get("sample_type") != "synthetic":
    raise ValueError("Expected a synthetic schema example")

records = sample.get("records")
if not isinstance(records, list) or not records:
    raise ValueError("Expected at least one record")

seen_domains = set()
for index, record in enumerate(records, start=1):
    issues = []
    if not isinstance(record, dict):
        print(f"record {index}: review; row is not an object")
        continue

    missing = sorted(REQUIRED_FIELDS - record.keys())
    if missing:
        issues.append("missing " + ", ".join(missing))

    domain = record.get("input_domain")
    if not isinstance(domain, str) or domain not in ALLOWED_HOSTS:
        issues.append("input_domain is outside the synthetic example hosts")
    elif domain in seen_domains:
        issues.append("input_domain appears more than once")
    else:
        seen_domains.add(domain)

    source_url = record.get("source_url")
    if not isinstance(source_url, str):
        issues.append("source_url must be text")
    else:
        if not is_synthetic_https_url(source_url):
            issues.append("source_url is outside the synthetic HTTPS hosts")

    observed_at = record.get("observed_at")
    try:
        if not isinstance(observed_at, str):
            raise ValueError
        timestamp = datetime.fromisoformat(observed_at.replace("Z", "+00:00"))
        if timestamp.tzinfo is None or timestamp.utcoffset() is None:
            issues.append("observed_at needs a timezone")
    except ValueError:
        issues.append("observed_at is not a timezone-aware ISO timestamp")

    status = record.get("field_status")
    if not isinstance(status, str) or status not in ALLOWED_STATUSES:
        issues.append("field_status is invalid")
    else:
        company_name = record.get("company_name")
        if status == "accepted" and (
                not isinstance(company_name, str) or not company_name.strip()):
            issues.append("accepted row needs non-empty company_name text")
        elif company_name is not None and not isinstance(company_name, str):
            issues.append("company_name must be text or null")
        if status != "accepted" and not record.get("review_reason"):
            issues.append("non-accepted row needs review_reason")

    outcome = "accepted" if status == "accepted" and not issues else "review"
    print(f"record {index}: {outcome}")
    for issue in issues:
        print(f"  reason: {issue}")

Expected output:

record 1: accepted
record 2: review

The second record includes a review reason, so the script should not print an additional reason. A local pass confirms only schema checks. It does not establish that a company exists, that a source supports a field, or that the row is suitable for CRM write-back. Python's datetime documentation explains aware timestamps, and URL parsing documentation warns that parsed components still need validation.

Set the review and write boundary

Agree the accepted-field list, source rules, null handling, refresh interval, expected volume, review capacity, and correction process before any delivery. Let a CRM operator inspect source evidence and approve each write; keep credentials and write permissions outside the sample and scoping email.

Estimate the pilot with the agreed record value, acceptance threshold, and review time. The synthetic rows do not support a coverage rate, match rate, time-saving figure, or return-on-investment claim.

Request a scoped discussion

The workflow email draft addressed to hello@proxylane.dev can include domains, fields, geography, refresh interval, format, volume, and acceptance rules. It opens for review and is not sent automatically. ProxyLane must confirm feasibility, scope, price, and acceptance criteria before work or purchase terms are agreed.

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