The system learns from recruiter edits and preferences—such as which channels work, what outreach performs, and when searches need widening—so best practices compound across the whole talent team.
Experienced recruiters provide the corrections, context, and standards the agents learn from. People define what good looks like and validate results before action is taken.
AI learns from which candidates recruiters advance or reject so future sourcing results better match the team’s definition of a strong profile.
hireEZ / SeekOutAI compares reply and conversion rates across templates and channels, then recommends better messaging patterns based on recruiter edits and outcomes.
Gem / hireEZAI aggregates recruiter activity and hiring outcomes into team dashboards so successful sourcing channels, response patterns, and workflow tweaks can be reused across reqs.
Ashby / GreenhouseI help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.
Design and build LLM-powered products and agentic systems
Go from idea to production with a clear implementation roadmap
Build AI with human-in-the-loop in regulated environments
hireEZ rebuilds its entire platform on agents. What your best recruiter knows, your whole team gets. The boring half of the job disappears, and the hunt and the close come back. See it live on stage at SpeakEZ Summit on August 27.