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AI outbound engine: Clay enrichment + LLM first lines

Rebuilding my manual Apollo → Instantly cold email workflow AI-first: Clay enrichment, ICP scoring and Claude-written openers, pushed into Instantly.

The problem

At Maildoso I ran cold email campaigns to lists of up to 100,000 prospects. List building, enrichment and personalization were the slowest parts, and generic first lines hurt reply rates.

The plan

  1. Pull an ICP list (title, company size, industry) from Apollo into Clay.
  2. Waterfall enrichment: company website, recent news, tech stack, hiring signals.
  3. Score every lead against the ICP and drop the bad fits before sending.
  4. Prompt Claude to write a one-line, fact-based opener per lead, with guardrails so it can’t make things up.
  5. Push qualified leads and their openers into an Instantly campaign.

What I’ll measure

  • Hours saved per 1,000 leads compared with the manual process
  • Reply rate against a non-personalized control group
  • Cost per enriched lead

Results

Coming soon.

Next build →

Webinar → content pipeline in n8n