The traditional process of business development in patent law is notoriously inefficient, often draining thousands of non-billable hours from high-stakes litigation teams.

Patent defense attorneys typically spend significant time every day manually scanning new court filings and conducting technical feasibility analyses for potential pitches. &AI, a legal technology startup, is addressing this bottleneck with the launch of "Opportunities," a real-time feed designed to automate the discovery and analysis of new litigation.

The platform delivers alerts as quickly as five minutes after an electronic filing occurs, allowing firms to react almost instantly to new threats against their clients. Beyond simple notifications, the tool employs data enrichment—the process of enhancing raw data with additional context—to link LinkedIn connections between law firm staff and the defendant's in-house counsel.

Furthermore, the system analyzes historical behavioral patterns, such as prior settlement rates and typical case durations, to help teams predict how a specific matter may unfold. By streamlining the identification of relevant patents and accused instrumentalities, the platform aims to convert non-billable research time into successful revenue-generating engagements.

The traditional process of business development in patent law is notoriously inefficient, often draining thousands of non-billable hours from high-stakes litigation teams.

Patent defense attorneys typically spend significant time every day manually scanning new court filings and conducting technical feasibility analyses for potential pitches. &AI, a legal technology startup, is addressing this bottleneck with the launch of "Opportunities," a real-time feed designed to automate the discovery and analysis of new litigation.

The platform delivers alerts as quickly as five minutes after an electronic filing occurs, allowing firms to react almost instantly to new threats against their clients. Beyond simple notifications, the tool employs data enrichment—the process of enhancing raw data with additional context—to link LinkedIn connections between law firm staff and the defendant's in-house counsel.

Furthermore, the system analyzes historical behavioral patterns, such as prior settlement rates and typical case durations, to help teams predict how a specific matter may unfold. By streamlining the identification of relevant patents and accused instrumentalities, the platform aims to convert non-billable research time into successful revenue-generating engagements.