Recruiting AI Showcase

Three recruiting technology vendors demonstrate their AI-driven products live, each facing an unscripted challenge question after their pitch.

The first demonstration features an AI interviewer that conducts candidate conversations directly, rather than matching keywords on a resume to a job description. It can interview candidates around the clock in nearly any language, having been trained on millions of past conversations with input from talent, ethics, and linguistics experts. Live on stage, it runs a mock interview for a recruiting operations role, then switches to a technical mock interview for a medical device sales job in Houston, showing how it produces scorecards with competency ratings, red flags, and a hire recommendation. A question from the audience prompts a discussion of how the tool can be configured to monitor for interview cheating, including screen sharing, extra people in frame, and use of outside AI tools during coding assessments.

The second demonstration covers an AI sourcing tool built on top of a note-taking product for recruiters. Fed a job posting or an intake call recording, the tool extracts requirements and drafts an "ideal candidate profile" that guides its search across a large candidate database, LinkedIn, GitHub, and an integrated applicant tracking system. Recruiters can edit the profile, give feedback on results, and relaunch searches with new instructions in plain language. Given a challenge to find an AI engineer in Portland skilled in several programming languages, the tool is shown reasoning through market conditions in that city before refining search criteria and surfacing candidates, functioning partly as a market-mapping assistant alongside its sourcing function.

The third demonstration introduces a communication platform built to speed up the interview and submission process for recruiters. It centers on removing friction from scheduling, conducting, and sharing interviews, with the goal of cutting weeks out of a typical hiring timeline through faster collaboration between recruiters and hiring teams.

Across all three demonstrations, common threads include reducing manual screening work, giving hiring teams richer signal on candidates before committing human time, and letting recruiters interact with the tools conversationally rather than through rigid filters or keyword matching.