lead-hunter

Lead-hunter automates end-to-end lead capture, qualification, and outreach workflows across multiple sources. It monitors your full pipeline, detects bottlenecks in real time, and triggers specialized skills to fix problems automatically, eliminating manual qualification steps and improving response times.

Yes. Lead-hunter runs A/B testing experiments automatically on lead workflows, measures conversion impact, and keeps improvements that work. It detects when conversion rates drop, spawns targeted skills like faster-response handlers, and validates results before deployment.

Lead-hunter generates automated intelligence on lead sources, agent performance, and pipeline velocity through real-time monitoring. It maintains a relational data model tracking leads, events, experiments, and spawned skills, enabling data-driven decisions without manual reporting.

The system continuously monitors lead pipeline performance, identifies efficiency gaps, and dynamically spawns specialized skills to address specific bottlenecks. It runs deterministic lead assignment and tracks results, ensuring improvements are validated before staying in production.

Yes. Lead-hunter is designed to solve inefficiencies in distressed-property lead generation, automating capture and outreach workflows for that domain. It applies to building adaptive lead systems across multiple sources, though the framework extends to other lead-generation contexts.

Lead-hunter requires structured lead data, defined conversion metrics, and integration with your existing outreach channels. It builds a relational data model internally, so you need to connect your lead sources and define which pipeline stages to monitor and optimize.