Finding buyers at the exact moment they need help

My client sells to local businesses at one specific moment: right after something goes wrong with their public listing. Reach them a day late and a competitor has the deal. Reach them on a false alarm and you've burned the lead, and your name with it.

A monitor that watches 38,548 business listings around the clock. When it spots the trigger, it doesn't raise the alarm. It holds the lead, checks again independently, and only then hands it to sales with the business details attached. Nothing reaches a rep that hasn't been confirmed twice. On top of that sits a weekly risk model that predicts which businesses are most likely to hit the trigger next, so the team can get ahead of it instead of reacting to it. And when a business signs, its record flows into the CRM pipeline in about two seconds, with nothing typed twice.

The engine produced a 51-lead pipeline in its first four days, every lead confirmed twice. In testing, the risk model's highest-risk tenth triggered 4.5 times more often than average. Sales now works a ranked list of real opportunities, and the whole system runs unattended.

Postgres, headless browser verification, Python, statistical risk scoring, n8n orchestration.