Peakzi AI provides artificial‑intelligence tools tailored for trade‑service businesses, helping them capture and retain organic traffic that would otherwise be intercepted by competitors. Its platform analyzes search and market signals to surface high‑value contractor leads, recommending only the top 1% while filtering out the rest, enabling companies to focus on the most profitable opportunities. Users such as plumbing and home‑service firms cite it as a valuable source of strategic business intelligence.
Funding
Funding not disclosed
Founders
Product
Problem
Trade contractors often lose high‑value homeowner inquiries because traditional search and advertising channels either bury them in low rankings or fail to surface them before competitors capture the lead. This results in missed revenue opportunities and inefficient marketing spend.
Solution
Peakzi AI applies machine‑learning models to incoming homeowner requests, evaluating factors such as project scope, location, and contractor performance history. The platform filters and ranks these inquiries, recommending only the top 1% of qualified contractors for each job. By delivering prioritized leads directly to contractors, Peakzi AI enables firms to focus on high‑value opportunities and avoid the noise of low‑quality prospects. The system also provides strategic business intelligence dashboards that show lead trends, competitive positioning, and performance metrics, helping contractors refine their marketing strategies and improve win rates.
Target Audience
Primary customers are trade contractors such as plumbers, electricians, HVAC, and remodelers who rely on inbound homeowner leads to grow their service business.
Features
- AI-powered lead scoring that ranks homeowner inquiries based on relevance and profitability
- Automatic filtering that surfaces only the top 1% of contractors for each request, making other firms invisible to the homeowner
- Real‑time lead delivery via web portal or API integration with existing CRM systems
- Business intelligence dashboard with analytics on lead volume, source attribution, and market competition
- Continuous model training using contractor performance data to improve recommendation accuracy over time