Built an automated yoga teacher discovery and enrolment pipeline for YOGI TIMES - sourcing teachers from public web data, verifying emails, and enrolling them into email sequences with zero manual effort.

The Problem

YOGI TIMES needed to grow its email list with verified yoga teachers worldwide, but had no scalable way to find them. Discovery was manual, emails were unverified, and there was no deduplication against the existing 150k contact database. Every new teacher added required multiple tools and manual steps - research, email lookup, verification, and enrolment - making growth painfully slow.

What I Built

An end-to-end discovery-to-enrolment system that finds yoga teachers from public sources, verifies their emails, and enrols them into marketing sequences — fully automated with pacing controls.

AI-powered discovery — Perplexity researches and identifies yoga teachers from public web sources based on configurable locations and search templates.
Deduplication — every new contact is cross-referenced against the client's existing 150k dataset to prevent duplicates.
Email finding & verification — Hunter locates business-domain emails only, then validates and filters to high-confidence results.
Queue management — 15-minute spacing control to stay within platform rate limits and maintain deliverability.
Automated enrolment — upsert to Systeme.io with "New Yoga Teachers" tag and sequence assignment.
Logging — all actions, errors, and counts tracked in a Make Data Store and Google Sheets for full visibility.

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Tech Stack & Features

Platform: Make (2 scenarios)

APIs: Perplexity AI, Hunter (find + verify), Systeme.io REST API

Data layer: Google Sheets, Make Data Store

Key modules: Routers, Filters, Iterator, Text Parser, Sleep (queue pacing), Break & Resume error handlers

Patterns: AI-driven research, deduplication against large dataset, email verification pipeline, rate-limited queue processing, upsert to external CRM, full audit logging

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