We're Building AI Agents that Diagnose Campaign Performance
Most lead generation tools operate on simple rules. We built an AI system that actually thinks about why a campaign is underperforming, not just whether it is.
Most lead generation tools operate on simple rules. If the reply rate drops, send more emails. If leads run low, scrape more contacts. If an inbox gets flagged, swap it out.
These rules work. They keep campaigns running. But they don't make campaigns better.
We wanted something smarter. So we built an AI system that actually thinks about why a campaign is underperforming, not just whether it is.
The Problem With Hardcoded Rules
Here's how most automated systems work:
- Lead count below 10%? Run a refill scrape.
- Open rate dropping? Check inbox health.
- Reply rate down? Increase volume.
This logic handles the obvious stuff. But it misses the nuance.
What if the reply rate is down because the copy isn't resonating with property managers? More volume won't fix that. What if the leads are fine, but you're reaching facilities directors when you should be targeting operations managers? Scraping more of the wrong contacts just burns through your list faster.
Hardcoded rules treat symptoms. They don't diagnose problems.
How Our Triage System Works
We call them triage jobs. The name comes from medical triage, where doctors assess patients and decide who needs what treatment. Our AI agents do the same thing for campaigns.
When a triage job runs, the agent looks at everything:
Performance signals
- Open rates, reply rates, interested response rates
- Trends over the last 7, 14, and 30 days
- How this campaign compares to similar ones
Content analysis
- Which subject lines are working
- Which email templates get responses
- Whether the copy matches the target audience
Infrastructure health
- Inbox deliverability scores
- Send volume distribution
- Domain reputation
Lead quality
- Are we reaching the right decision-makers?
- Which property types are responding?
- Is the geographic targeting too broad or too narrow?
Then the agent makes a judgment call. Not just "something is wrong," but "here's what's wrong and here's how to fix it."
From Diagnosis to Action
The triage system doesn't just write reports. It executes.
If the diagnosis is "copy isn't resonating with this audience," the agent can draft new email templates, A/B test them, and shift volume toward what's working.
If the problem is lead quality, it can adjust the targeting parameters and queue up a new scrape focused on different property types or job titles.
If inbox health is the issue, it can rotate in fresh inboxes from our reserve pool before deliverability tanks.
The key difference: the system understands context. It doesn't just react to numbers dropping below a threshold. It asks why the numbers dropped and picks the intervention most likely to help.
Why This Matters for Contractors
You probably don't care about the technical details of how our AI agents work. That's fine. Here's what it means for you:
Faster optimization. We catch underperforming campaigns earlier and fix them before you notice a problem.
Smarter fixes. Instead of just "send more emails," we figure out the actual issue—whether that's targeting, messaging, timing, or deliverability.
Less waste. We don't burn through your lead list with the wrong approach. If something isn't working, we change strategy before exhausting good contacts.
Continuous improvement. Every campaign teaches the system something. The triage agents learn which fixes work for which problems, so optimization gets better over time.
The Bigger Picture
Lead generation isn't just about volume. Anyone can blast 10,000 emails. The hard part is reaching the right people with the right message at the right time.
That requires judgment. And judgment is exactly what most automation lacks.
We're building AI agents that don't just follow rules. They evaluate, reason, and adapt. When a campaign underperforms, they don't just turn up the dial. They figure out which dial to turn.
It's the difference between a thermostat and a mechanic. One reacts to temperature. The other understands how the whole system works.
That's what we're building at Maverick. Not just automation, but intelligence.

Founder, Maverick AI
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