# Campus and early-career recruiting

A batch of interview invites goes out to a sourced list from a career fair or target school, every student completes the same AI interview without needing a resume of prior work experience to be evaluated against, and a recruiter builds a shareable shortlist from whoever scores well instead of reviewing raw applications one by one.

Campus recruiting has a shape that doesn't match most hiring processes. A hundred students collect at a career fair table in an afternoon, everyone has roughly the same amount of work experience, which is to say close to none, and the recruiting window closes on the school's calendar, not the company's.

## Why campus recruiting doesn't fit a normal screening process

Screening usually leans on work history: what someone did at their last job tells a recruiter a lot in a short amount of time. Campus candidates mostly don't have that. A resume built around a GPA, a couple of class projects, and a part-time job doesn't differentiate a strong candidate from a weak one the way a few years of relevant work experience would, so filtering on resume content alone tends to filter on school prestige or resume-writing skill instead of anything closer to actual ability. The volume problem compounds it: a career fair or campus event generates names faster than any individual outreach process, and by the time a recruiter is back at their desk, the momentum from meeting someone in person has usually faded before a follow-up call gets scheduled. What campus recruiting actually needs is a way to get every name from that list into a real conversation quickly, evaluated on something other than resume formatting, while the recruiting window is still open.

## How the pipeline applies to a sourced campus list

1. **Turn a sourced list into a batch of interview invites** — Names collected from a career fair, info session, or target-school outreach get a direct interview link sent as a batch, so no one has to individually apply through the job board first.
2. **Run a general interview when there's no resume to work from** — A general AI interview doesn't require a job description or resume, covering background, motivation, and behavioral situations, which fits a pool where prior work history is thin or nonexistent for most candidates.
3. **Rules filter on communication and behavioral scores, not experience** — Since experience-level fields carry less signal for this pool, screening rules built around communication and behavioral score thresholds do the filtering work that a resume-based rule would do for an experienced hire.
4. **Build a shareable shortlist for the recruiting team** — A curated list of the students worth a next step gets built by hand and shared with the campus recruiting team or hiring managers through a public link, with tracking on whether it was actually opened.

## Features that matter here

- [Batch interview invites](/features/interview-invites) — A direct interview link sent to an entire sourced list at once, so a career-fair name list becomes real interviews without individual applications first.
- [General AI interviews](/features/general-job-interviews) — A standard interview that doesn't require a job description or resume, matched to a candidate pool where prior work history is thin.
- [Automated screening rules](/features/screening-rules) — Filtering built around communication and behavioral scores instead of experience-level fields that don't carry much signal for early-career candidates.
- [Curated candidate lists](/features/curated-lists) — An ordered list built by hand and shared with a recruiting team or hiring manager through a link, with open tracking on whether it was actually reviewed.

## Frequently asked questions

### Do students need to have applied to a specific job posting first?

No. A batch interview invite sends a direct interview link to a sourced list, so a name collected at a career fair or info session can complete an interview without going through the job board application flow.

### What interview type works for candidates with little or no work history?

A general AI interview doesn't require a job description or resume and covers background, motivation, work style, and behavioral situations, which suits a pool where most candidates have similar, limited prior experience.

### How does screening work without much resume content to filter on?

Screening rules can be built around interview scores, communication and behavioral in particular, rather than experience-level or resume-keyword fields that don't differentiate much in an early-career pool.

### How does a recruiting team review results from a large batch?

A curated list can be built by hand from whoever interviewed well and shared with the recruiting team or hiring managers through a link, with tracking on whether it was opened.

### Can invites go out to a list gathered outside the job board, like a career fair sign-up sheet?

Yes. A batch interview invite works from any sourced list of names and contact information, so a paper sign-up sheet from an event can turn into real interview links the same day rather than waiting for those students to find and apply to the posting on their own.

## Related pages

- [Structured interviews at scale](/use-cases/structured-interviews-at-scale)
- [Improving candidate experience](/use-cases/candidate-experience)
- [Frequently asked questions](/faq)
- [Browse open jobs](/jobs)

## Turn a career-fair list into real interviews the same week

Send a batch invite to your sourced list and get every student into an AI interview before the recruiting window closes.

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