Managed application review
Your best applicants get rejected before anyone reads them.
Pond embeds a reviewer pod with your recruiting team and reviews 100% of applications the same business day. AI drafts, a named reviewer signs, and nobody exits without an interview.
Same day
Median time to review under Pond's SLA. The industry median is 17 days.
100%
Of applications get a human-signed decision. None sit unreviewed.
10 to 15 min
Adaptive interview for every candidate you'd otherwise reject unseen.
The problem
Nobody is reading the applications.
Recruiters are busy sourcing, running events, and chasing referrals. That work matters, which is exactly why review keeps sliding. So applications pile up for weeks, and the filter clears most of them out before anyone looks.
between a candidate applying and anyone looking. No SLA, no accountability for the wait.
of qualified applicants get auto-rejected without a human ever opening the file.
own the outcome. Review tools exist and go unused, because review isn't actually anyone's job.
Who the resume screen misses
The filter fails on predictable patterns:
- Self-taught engineers whose resumes undersell what they've built
- Career switchers whose experience doesn't map to the job title
- People who fail keyword filters on wording, not ability
- Candidates flagged as overqualified and quietly dropped
How it works
We take the applicant pool off your hands.
On the surface, Pond looks like a staffing service. Underneath, it's heavily automated. What you actually buy is the result: every application reviewed, every business day.
Embed
We assign an account rep and a reviewer pod, typically three reviewers, who work alongside your recruiting team. Your rep joins your weekly pipeline review.
Connect
The pod connects Pond to your ATS, Greenhouse or whatever you run. Pond drafts each screening summary, and a named human reviewer signs itbefore it's logged back to your ATS.
Review everything, same day
Every application gets a decision the same business day. Qualified candidates advance straight to your team, and nothing sits in the queue waiting for someone to find a spare hour.
The AI Interview Gate catches the rest
The gate picks up everyone marked not a fit: a structured 10 to 15 minute adaptive interview before they exit. Gems return to your pipeline. Everyone else is archived with written feedback.
Scale with your volume
When hiring ramps, we add reviewers to the pod, not overhead to your team. Same account rep, same weekly pipeline review, and the SLA never moves.
Two funnels
Same applicants. Very different endings.
The usual funnel
- Reviewed
- A fraction, weeks late
- Recovered
- None
- Candidates told
- Nobody
Ending: silence. The candidate hears nothing, and you never find out who you lost.
The Pond funnel
- Reviewed
- 100%, same business day
- Recovered
- Every gem the gate finds
- Candidates told
- All of them, in writing
Ending: interviews, offers, and hires recovered from your own reject pile.
The AI Interview Gate
Nothing gets thrown away.
Resume screens judge paper. The gate judges the person. Every rejected candidate gets a structured, adaptive interview before they exit, and the strong ones come back.
Gems come back
Candidates whose resumes undersold them are promoted back into your pipeline, where they can go all the way to in-person interviews and an offer.
Everyone else gets an answer
Candidates the gate doesn't promote are archived with written feedback. An interview and a real answer, instead of the silence they'd get anywhere else.
It adapts to the candidate
There's no fixed script. The gate follows the candidate's actual experience, digs where the resume is thin, and writes up findings your team can check.
How a gem gets found
Nina Petrova, a self-taught engineer with no CS degree, gets marked not a fit at the resume screen. In the usual funnel, that's the end of her file.
The gate interviews her instead. Fifteen minutes in, it surfaces something no keyword filter would: she architected a real-time bidding system handling 800k queries per second.
Promoted back to team interview, with the findings attached.
Illustrative scenario from the Pond product demo.
hires this quarter came through the gate in our demo workspace, recovered from a reject pile the client already owned.
Pricing
You'll have a number on the first call.
No two applicant pools look alike, so we quote yours directly instead of publishing a rate you'd have to reverse engineer.
Pond · Managed Review
Quoted per pool
Your account rep walks through the numbers on the call.
Every engagement includes
- A reviewer pod of three, embedded with your team
- An account rep in your weekly pipeline review
- Pond connected to the ATS you already run
- 100% of applications reviewed, same business day
- Human-signed decisions logged back to your ATS
- The AI Interview Gate on every rejection
- Written feedback for every archived candidate
Why this works
The outcome is the product.
Review software still needs a recruiter with a free afternoon. Pond doesn't. A pod owns your queue, and we're measured on the hires that come out of it.
A pod owns the queue
Competitors sell software that recruiters never get around to opening. Pond's reviewers sit inside your team, and the queue is their whole job.
Human-signed, AI-powered
Every screening summary reads "Drafted by Pond, confirmed by a named reviewer." You get same-day speed without an algorithm rejecting people on its own.
Nothing gets discarded
The gate interviews every rejected candidate. You recover hires from your own reject pile, and candidates get feedback instead of silence. That's worth something to your pipeline and to your reputation.
Aligned incentives
We're measured on the hires that come out of the pool we review, not on headcount. If we don't surface people you want to hire, we haven't done the job.
Get started
Hand us your applicant pool.Every application, reviewed by tomorrow.
A pilot takes one ATS connection and one pod. Your queue will be fully reviewed before the week is out, and your account rep walks you through pricing on the same call.