Atlas Global Solutions

Growth engine

Lead research & enrichment

Find the right people at the right companies, with the context your sales team would spend hours digging up.

An AI pipeline that takes a target profile, finds matching companies, finds the right person at each one, pulls real context from public sources, and hands your sales team a hot list. The work that nobody enjoys but everybody needs.

Typical price

Setup fee $499+, credited back against your first performance fees. After launch, common performance models for this engine: pay per qualified lead delivered, or pay per qualified meeting booked.

Typical timeline

2 to 3 weeks to first hot list. Weekly delivery thereafter.

How we build it

Stage 1

Define the target

We work with you to define an ideal company profile and an ideal person profile. Tighter is better.

  • Industry, headcount, geography, revenue band, technology used
  • Person seniority, function, tenure signals, recent posts or moves
  • Negative filters (companies and roles to skip) included
Stage 2

Find companies

AI searches across public sources for companies matching the profile. Volume is the easy part. Quality is the hard part.

  • Multi-source search (LinkedIn, company directories, industry databases)
  • Auto-deduplication across sources
  • Funding and headcount signals where available
  • Negative-filter pass to remove obvious bad fits
Stage 3

Find people and pull context

For each qualified company, find the right person and gather context worth bringing into a conversation.

  • Decision-maker identification at each company
  • Recent public statements (podcasts, blog posts, social) summarized
  • Mutual connections or relevant signals surfaced
  • One-paragraph context note per lead
Stage 4

Deliver

A weekly hot list to your CRM, ready to work. No spreadsheets, no copy-paste.

  • Direct write to your CRM with custom fields
  • Weekly email summary to the sales lead
  • Per-lead source citations included
  • Quality feedback loop (reps mark good and bad leads, AI learns)

Edge cases

  • LinkedIn-only intent. We use compliant licensed providers, never raw scraping at scale.
  • Highly regulated industries. We add a compliance pass on context summaries.
  • Tiny target market. We don't run this if there are fewer than ~500 plausible accounts. The math doesn't work.

Related reading

Related guides

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