We're building the recruiter that knows people are more than a resume.
Semantic Recruitment is the parent company behind Yeats — an AI recruiting platform built around whole-person matching, not resumes and keyword filters. Traditional recruiting is a one-time transaction. Yeats never stops working on your behalf.
The Who, What & Why
Who We Are
Semantic Recruitment was founded in 2025 by two people who'd spent enough time around recruiting — one from 25+ years inside the industry, one from brand, product, and operations — to see exactly where it kept failing people. We started the company to build the thing we wished already existed: a recruiting platform that treats matching as an ongoing relationship, not a single transaction that ends the moment someone's hired or passed over.
Our mission is straightforward: perfect job matching through AI automation. Our vision is bigger than that — a world where everyone has their dream job. Getting there starts with the fundamentals most companies skip. We're a Delaware C-Corporation based in Phoenix, Arizona, and from day one we've treated compliance and data governance as core architecture, not a checkbox added after the fact. Every data source we use, every piece of outreach we send, is reviewed and documented before it ever touches a real person's inbox.
What We Do
We're building Yeats — an AI recruiting platform that automates the parts of hiring that were never suited to manual work, while keeping every decision that actually matters in human hands. Yeats learns continuously from both sides of the table: what a person actually wants out of their career, not just what their resume says they've done, and what a company genuinely needs, not just what a job posting lists. That picture keeps updating as circumstances change, instead of freezing the moment an application gets submitted.
The result is matching that looks nothing like keyword filtering. Where traditional tools sort people into pass/fail buckets based on the words on a page, Yeats is built to understand the whole person and the whole role, and to keep refining that match over time rather than making one guess and walking away. We automate the searching, the sorting, the repetitive back-and-forth — the parts that were always better suited to a tireless system than a human recruiter running on hour six of the same task. We don't automate the decisions that should stay human: who gets hired, who takes the offer, who the right fit really is. That call is never ours to make.
Why We Do It
Traditional recruiting runs on a strange kind of waste. Qualified people stay unemployed while the right roles for them sit open for months, not because a match doesn't exist, but because the tools in between were never built to actually find it. A resume gets reduced to keywords, a keyword search misses the person it should have caught, and everyone involved — job seeker, employer, and the recruiter stuck manually bridging the gap — pays the cost of a system that treats matching as a filtering problem instead of an understanding problem.
That's been true for a long time. What's changed is that AI has only recently reached the point where real, continuous, whole-person matching is actually possible to build — not as a research demo, but as something that can run reliably, transparently, and at scale. We didn't start Semantic Recruitment because the timing was convenient. We started it because the timing finally made the thing we wanted to build possible at all.
Why Now
AI capabilities have finally reached the point where perfect job matching is actually possible — not as a research demo, but as something reliable enough to build a company on. Agentic AI can hold a real conversation, retain context over time, and keep working on someone's behalf continuously, rather than answering one query and stopping. Five years ago, the technology simply couldn't do that. Today it can, and that gap between "not yet" and "now" is exactly why Yeats exists on this timeline and not another one.
This isn't a market Yeats is trying to create — it's one that's already waiting, and the window to build for it well is now, not later. Every year this capability existed without a company built specifically around it was a year the $474B recruiting industry kept running on tools that were never built to actually understand the people and roles they were matching. We didn't wait for someone else to close that gap. We started building the moment it became possible to build right.
Meet The Team
The Founders
Jesse Hogan — Co-Founder, CEO & CTO
Jesse brings 25+ years of technical experience as a developer and architect to Semantic Recruitment's foundation, leading Yeats' engineering, matching logic, and system architecture. He's spent his career watching recruiting systems get built the wrong way — bolted together, scaled past their limits, patched instead of rebuilt. YEATS is what happens when that same experience gets to start from the ground up instead of cleaning up after the fact.
Delia Hogan — Co-Founder & CXO
Delia brings a marketing background to Semantic Recruitment's compliance, brand, product design, and user experience — the full range of work that turns a good idea into something people actually trust and want to use. She calls her role "bringing order to chaos," and in practice that means everything from the company's visual identity to the compliance framework governing how Yeats reaches people in the first place.
Team Members
Martin Morales — Principal Backend Engineer
Martin is a U.S. Army veteran with three combat deployments who brought that same discipline into a career spanning financial infrastructure at Nasdaq, cloud migrations, and production AI systems — including a retrieval-augmented generation platform that gives real-time insights across farms managing hundreds of thousands of animals. He's built systems that have to work under real constraints: real money, real scale, real cost limits. That's the standard Yeats is held to.
Ryan Rollins — Senior Backend Engineer
Ryan spent nearly a decade at Electronic Arts building automated testing infrastructure for Apex Legends, including a full-stack platform that ran hundreds of automated tests daily for a game played by over 100,000 people. He also led the integration of a large language model for automated root cause analysis — teaching a system to triage bugs the way an experienced engineer would. That same instinct for building systems that do the tedious work reliably is exactly what Yeats needed.
Seeking Investment
The Opportunity
We are approaching MVP launch and beginning seed conversations now. The technical foundation is in place, the team is assembled, and we are building on a launch-early, iterate-often model — Yeats gets better the moment it starts working with real people.We are looking for seed investors and strategic advisors who bring more than a check. If you have experience in recruiting industry transformation, AI product development, or B2B marketplace scaling, we'd like to talk. We're selective about who comes in early, because the right partners at this stage matter as much as the capital.
Connect with us!
Semantic Recruitment on LinkedIn