Building an AI Automation That Finds and Verifies Business Owner Emails

I recently worked on an automation where the input was simple but the logic was not.

A Google Sheet from Outscraper containing business names and addresses. Sometimes a website. Sometimes a phone number. Emails were often wrong or missing.

The goal was to enrich every single row without skipping anything.

The workflow runs row by row in n8n. Even if an email already exists, the automation still rechecks the business. No assumptions.

First step is controlled HTTP scraping. If a website exists, the automation checks key pages like homepage contact about and team. Text is capped and cleaned immediately to avoid token overload.

Next comes AI reasoning. Instead of free text responses, the model is forced to return strict JSON only. Owner name email source confidence and notes. If the owner cannot be found, it returns blanks with a reason. No hallucinations.

Email extraction happens from both scraped pages and AI inference but nothing is trusted yet.

Every email then goes through Reoon verification with daily rate limits enforced. Batch control makes sure we never exceed the quota. Failed verifications are logged not retried endlessly.

The sheet is updated in place. Correct columns only. No overwriting without intent. Idempotency checks prevent duplicates and infinite loops.

Failures do not crash the workflow. HTTP errors timeouts missing websites all fall into a handled path with logs.

End result is a clean verified CSV that can actually be used.

Outscraper sheet in. Owner name and best email out. Verified. Logged. Reliable.

This type of automation is where AI is useful only when the guardrails are tight.

2 comments