Use case

AI tool to qualify leads automatically

Every new lead means the same research loop: check the company, check the role, check the signals, decide if it's worth a sequence. Agencize turns that judgment into a playbook, then runs it as an Instant App that researches, scores, and drafts outreach — so your queue starts with qualified leads and a drafted opener, not a spreadsheet of names.

This playbook came from real research, not a generic ICP template

This isn't a generic lead-scoring template. It's a playbook learned the same way every Agencize playbook is — by watching what a salesperson actually does while researching a prospect and talking to AI about whether it's worth pursuing, then capturing the rules behind that call. See how playbooks are learned for the general mechanism. Here's what that looks like once it's been distilled for lead qualification.

This is what the playbook actually contains.

Agencize AI learns these rules while you talk through real prospect research: which accounts you skip, which signals change your mind, where you correct the AI, and how you shape the opener before it goes to a human for review.

Lead qualification playbook

Inbound lead qualification — 5 rules

01

Skip companies under 50 employees

Check headcount before doing any deeper research.

02

Require B2B SaaS or an adjacent model

Check the company's site and LinkedIn description against the target business model before scoring anything else.

03

Score up on a recent funding signal

Check Crunchbase for a raise within the last 12 months — Series A or later.

04

Flag for review if no VP-level contact is found

If the lead list doesn't include a decision-maker title, don't disqualify — flag it for a human to find the right contact.

05

Draft the opener around a real, recent signal

Reference the specific funding news, a product launch, or a hiring spree — never a generic compliment.

None of these five rules came from a best-practices guide. Each one exists because a specific lead got judged once, in a real research session, and the playbook kept the reasoning.

What you actually get

Here's what runs on every new lead instead of you.

Prospect Intelligence / Lead Qualification

Runs on every new lead

Prospect Intelligence

Connected: LinkedIn · Crunchbase · CRM — last synced 9 minutes ago

Queue ready

Leads checked

38

Qualified

14

Openers drafted

14

Needs review

3

Lead
Signal found
Fit
Status
Acme Robotics
Raised Series A, 3 weeks ago
Qualified
Day 1 opener drafted
Bramble Co
12 employees
Below size floor
Disqualified (Rule 1)
Nimbus Analytics
No VP-level contact found
—
Needs your review (Rule 4)
Forge Systems
Hiring for 4 sales roles
Qualified
Day 1 opener drafted

Bramble Co never reaches a human — it's disqualified before any time gets spent on it. Nimbus Analytics isn't thrown away either; it's flagged because the playbook found a good-fit company but couldn't find the right person, which is exactly the kind of gap a rep should close, not skip. The two qualified rows already have a drafted opener waiting for review, built around the specific signal that qualified them.

What this replaces, and what it doesn't.

Versus a lead database like Apollo or ZoomInfo

A database gives you contact data and firmographic filters, but the judgment of who's actually worth pursuing is still yours to apply by hand, lead by lead. This applies that judgment automatically, using rules learned from how you actually qualify, not just a filter panel.

Versus an SDR doing the research manually

An SDR brings judgment, but you're training them on what counts as a good fit and reviewing their calls regardless. This starts from judgment that's already been demonstrated and captured, so qualification is ready before anyone opens a tab.

Versus a generic AI outreach tool

A generic outreach tool can draft a message, but it doesn't know who's worth messaging in the first place — it'll happily personalize an opener for a lead that should've been disqualified. This ties the draft to the same rules that did the qualifying.

Lead qualification FAQ

Will it send outreach without me reviewing it first?

No. It drafts the opener and queues it for review — nothing goes out until you approve it. You stay the one deciding what gets sent; the app removes the work of researching and drafting it.

What if my ICP doesn't match the example shown here?

It will, and that's expected. The five rules shown are one rep's playbook, learned from how they actually qualify leads. Yours gets built the same way — from your own fit criteria and your own corrections — not copied from this example.

Does this replace my SDR team?

It replaces the repetitive part of qualification — checking firmographics, scanning for signals, drafting the first pass. The judgment calls that don't fit a rule yet, like the flagged contact gap, still come to a person.

How is this different from a tool like Apollo or ZoomInfo?

Those tools are where the data comes from. This is what happens after the data — applying your specific qualification judgment to it automatically, instead of leaving every lead for a person to evaluate one by one.

Related reading

How a solo agency handles 100+ leads a day without hiring an SDR

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