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250 CVs per role. Interview the right 25.

The AI reads every CV against your job description, adds what's public on LinkedIn, and gives HR one page ranking who to interview first. No more interviewing 100 people to fill 10 seats.

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Shortlist · Sales executive250 CVs read
  • 92Riya Mehta5 yrs B2B sales, CRM, GujaratiInterview
  • 84Arjun NairField sales, beat the target 3 quartersInterview
  • 61Karan PatelRetail counter sales, no B2B
  • 38Sneha IyerMarketing intern, no sales

Sample data. Names and numbers are made up.

Same job. Far fewer hands on it.

Here's how the work usually runs today, and how it runs once the system is in place.

The usual way

  1. 017 to 10 days to screen a role
  2. 02100 to 150 interviews to fill 10 seats
  3. 03CVs read in the order they arrived
  4. 04Strong candidates lost in the pile
  5. 05Every recruiter screens differently

With Aivaura

  1. 01Screening done in minutes
  2. 0220 to 25 interviews to fill 10 seats
  3. 03Every CV read against the real JD
  4. 04The best fits rise to the top
  5. 05One consistent score for everyone

What it actually does.

Reads

Every CV, not the first fifty.

Each CV is matched against the actual job description, including the skills hidden in project descriptions.

  • JD to CV matching
  • Skills and experience
  • Must-have checks
  • PDF and Word CVs

Enriches

Fills in what the CV leaves out.

Public LinkedIn details and other open information complete the picture.

  • LinkedIn profiles
  • Career history
  • Gaps flagged
  • Location and notice period

Ranks

One page HR can act on.

A ranked shortlist with the reasons behind each score, ready to send to interviews or the AI interviewer.

  • Ranked list
  • Reasons per candidate
  • Shortlist export
  • Feeds the AI interviewer

Where teams use it.

High-volume roles

The problem
Hundreds of applications for each opening.
What we build
Every CV scored and ranked as it arrives.
What changes
Interviews go to the strongest candidates first.

Campus and bulk hiring

The problem
Thousands of student CVs with similar profiles.
What we build
Scoring on the skills that actually predict fit.
What changes
A fair, fast shortlist from a huge pool.

Works with what you already use.

  • Email inbox
  • Google Drive
  • Naukri exports
  • LinkedIn
  • Google Sheets
  • Your ATS by API

Common connections. The exact list depends on your setup.

Often built for.

See it in a real project.

A hiring team filling multiple roles

250 CVs per role. Interview the right 25.

The problem250 CVs a role, and 100+ interviews to fill 10 seats.

What the agent doesReads every CVChecks LinkedInRanks

Read the full story

What they got

Interviews to fill 10 seats
100 to 15020 to 25
Screening a role
7 to 10 daysMinutes
CVs scored per role
About 250
  • 10 seats filled with 20 to 25 interviews instead of 100 to 150
  • Screening that took 7 to 10 days now takes minutes

Fair questions.

Is it fair to candidates?

Every CV is read against the same job description and criteria, which is fairer than reading the first fifty that arrived. HR always makes the final call.

Can it work with our existing ATS?

Usually, yes. It can read from your inbox, a shared folder or your ATS, and write the ranking back.

Does it replace interviews?

No. It decides who to interview first. Pair it with the AI interviewer to take the interviews too.

Request a demo of AI resume screening.

Leave your details and we'll set up a live walkthrough, ideally on a few examples from your own business.

Other things we build