Detect risky clauses in leases and contracts with per-document AI review

Small and medium businesses, property managers, and HR teams routinely sign leases and contracts without affordable legal review, exposing them to hidden liabilities like unfavorable renewals, indemnities, and surprise fees. These organizations face frequent, material risk — missed termination windows, unanticipated obligations, and disputes — that hourly counsel is too expensive to solve at scale. Build a per-document AI review that extracts clause-level elements, flags risky provisions (red/yellow/green), and delivers a one-page plain-language summary and suggested edits, accessible via web upload, email, and API with optional human escalation for high-risk files. Offer a pay-per-document option plus a subscription tier aimed at higher-volume SMBs to match the $3K ACV economics many buyers can absorb. The timing is right: roughly 3M addressable businesses × $3K ACV yields a $9.0B market, and improvements in model accuracy and cost make clause-level extraction practical for non-enterprise customers (market score 88/100, revenue potential 80/100). SMB demand for fast, affordable contract triage and the opportunity to verticalize (leases, employment, regulated sectors) give a clear path to traction. You can differentiate through verticalized templates, curated rule sets, and a human-in-the-loop audit trail to deliver enterprise-grade precision at SMB prices, but success hinges on building training data, proving accuracy, and establishing a clear liability/insurance model. If you solve trust and precision, this can capture underserved SMB legal spend quickly; if not, false positives and legal risk will constrain adoption.