B2B Lead Intelligence Engine

Outbound teams spend more time researching companies than speaking to them. This build automates discovery, research and scoring, and drafts messages from verified facts only.

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Challenges

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Manual prospecting is slow and inconsistent. Research varies by person, generic messages get ignored, and opt-outs and source records are easy to lose track of.

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Solutions

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A pipeline discovers companies in a target niche, enriches each one from its public website into a structured profile, scores fit against an ideal customer profile, drafts messages that cite stored facts, and manages replies and opt-outs.

What the system does

• Discovers companies in a chosen niche and region through search and maps data, and removes duplicates by domain.

• Reads each company’s public website, respecting robots.txt and site terms, and extracts services, size signals, technology hints and public contact routes.

• Stores every fact in a structured profile with its source link, so each claim can be traced.

• Scores fit with weighted rules plus a written explanation, and sends borderline cases to a human review queue.

• Drafts first-line and follow-up messages, and rejects any draft that uses a detail not found in the stored profile.

• Pushes approved messages to a sending platform through its API, checks a suppression list first, and respects sending windows by time zone.

• Classifies replies (interested, not now, wrong person, out of office, unsubscribe) and suppresses unsubscribes immediately.

• Shows the funnel from discovery to reply, cost per qualified lead and data freshness.

Stack

n8n · Supabase (Postgres, pgvector) · search and maps APIs · language models selected per task · Instantly or Smartlead API · Next.js dashboard · Docker on ETHIOR’s own server.

Status and results

Designed, built and tested by ETHIOR. This is a reference build, not a client engagement. It is currently in development. The figures above are design targets, not results. They will be replaced with measured results, with sample sizes and dates, once the system is running.

Limits

Public data can be out of date, and scoring reflects the rules set. The public demo sends only to test inboxes. The system is built around UK PECR, US CAN-SPAM and Australian Spam Act requirements, and any real campaign needs legal review first.