What this solves

Manual lead research usually breaks in two places: the criteria are fuzzy, and the output is too inconsistent for a salesperson or founder to trust. AI can help, but only if the research workflow has sources, scoring rules, and a review point.

This offer builds a repeatable research and qualification system without handing outbound judgment to a bot.

What we build

An ICP and signal map: target segments, disqualifiers, trigger events, and source rules.
A research workflow that gathers only allowed public or approved data sources.
A lead brief format with cited signals, qualification notes, and recommended next action.
A handoff path into the CRM, sheet, or sales queue your team already uses.

Deliverables

Lead source map and qualification rubric.
Reusable research workflow for batches or recurring monitoring.
Qualified lead handoff template with enough context for human review.
Guardrails for outreach prep: what the system may draft, and what a human must approve.

What we need from you

Target customer profile, exclusions, and examples of good and bad leads.
Existing lead sources, CRM fields, outreach process, and handoff owner.
Any rules around geography, industry, privacy, scraping, or do-not-contact lists.
A small sample batch for testing before the workflow is trusted.

Risks and constraints

Do not use this to spray generic outreach at strangers. The useful version improves research quality and sales focus. It still needs a human to decide whether the account is worth contacting and what should be said.