Thousands apply. You still hire in days.
Reena is built for intakes where thousands apply and speed still matters: AI CV screening reads and ranks every application within minutes of arrival, AI interviews and self-booked scheduling run fair rounds at any volume, and bulk actions with automation clear the admin in between. Misk Foundation runs 10,000+ applicants per cycle in 2–3 weeks; CNTXT AI cut time-to-hire from around two weeks to 3–6 days.
When thousands apply, what has to give?
The usual answer is: something. Either the pile gets a fast, shallow read and consistency slips, or it gets a careful read and weeks disappear. On a manual process the first two hundred applications get real attention and the last two thousand get a few seconds each, so the outcome depends on where a candidate landed in the queue rather than on what they wrote.
Speed and fairness are not a trade-off at volume: they are both a system problem. While your pipeline waits, the strongest candidates accept the offer that moved first, and the admin breaks alongside them: every stage move, status update and rejection note multiplies by the size of the intake.
How does every application get a fast, fair read?
Reena reads every application within minutes of arrival, against the requirements your team sets, requirement by requirement, and returns a ranked shortlist with the reasoning beside every score. The speed comes from reading in parallel, not from skimming, and the read does not degrade with volume: the ten-thousandth CV is weighed exactly as the first.
Recruiters open the pipeline to a shortlist that is already prioritised, and everyone screened lands in a searchable talent pool ready for the next cycle. Cut+Dry in the United States reached qualified shortlists around 50% faster once screening moved to Reena, and CNTXT AI in the UAE saved 60–75% of screening effort.
How do fair first rounds happen at any volume?
Reena runs real-time voice interviews on the question set your team writes, asks adaptive follow-ups, and is available around the clock in any timezone, so a thousand first rounds can happen in the time one interview panel used to take.
Integrity checks flag scripted answers and environment tampering, and every outcome is reviewed by your interviewers: no candidate advances or exits on the AI's word alone.
What removes the scheduling back-and-forth?
For the rounds that need a human, candidates book their own interviews from live availability: Reena reads your interviewers' Google and Microsoft calendars for free and busy time, offers real slots in the candidate's own timezone, and sends confirmations, reminders and calendar invites automatically.
A booking that used to take a three-day email thread takes one click, and Reena reads only free or busy status, never event titles or attendees.
Who clears the admin and the idle gaps between stages?
Bulk actions handle the work that multiplies with volume: stage moves, qualify and disqualify decisions, tagging, sharing and CSV export run across hundreds of candidates at once. Automation rules take the rest, moving candidates forward or applying your knockout criteria the moment scores arrive, at two in the morning as reliably as two in the afternoon.
This is where large intakes get their time back: Misk Foundation cut manual screening workload by 50–70% and reduced administrative effort by around 60% across programme cycles that draw more than 10,000 applicants. Every automated action is recorded and reversible.
Speed and scale from the AI. Judgement from your team.
Nothing about moving faster or handling more removes judgement. That is a design rule, not a promise.
Every requirement, threshold and knockout rule is one your team wrote, and Reena runs on them at any speed and any volume.
Each recommendation and each automated step arrives with the reasoning behind it, logged where your team can see it.
Recruiters review, adjust and decide. Any call Reena makes, your team can override.
What faster at scale looks like on real hiring.
Measured on client hiring, not benchmarks.