AI Lead Processing System

The Problem

Leads come in through a form, but someone still has to read each submission, decide if it's a real fit, look up additional context, and manually enter it into a CRM or forward it to the right person.

Existing Workflow

Leads land in an inbox or spreadsheet. A team member manually reviews each one, does a quick check on the company, decides whether it's worth pursuing, and types the details into the CRM.

The Solution

New submissions trigger a workflow that structures the raw form data, enriches it with publicly available company information, and uses AI to score the lead against defined qualification criteria. Qualified leads are written directly into the CRM and the assigned owner is notified; anything below the threshold is flagged for manual review instead of being silently dropped.

Automation Architecture

Form/webhook trigger -> data structuring -> enrichment lookup -> AI qualification against defined criteria -> CRM record creation -> owner notification, with a manual-review queue for borderline cases.

Before vs After

Results

• Removes manual data entry for leads that pass qualification.
• Gives every lead a consistent qualification check instead of relying on whoever picks it up that day.

Limitations

Qualification criteria have to be defined clearly up front — the system is only as good as the rules and data it's given. Borderline leads are routed to a human queue rather than auto-decided.

Lessons Learned

Building in a manual-review path for borderline cases mattered more than trying to make the AI decide everything — it kept the team's trust in the system.