Candidates debug, refactor and speed up a deployed service, in a full repository, with their own editor and AI tools. You see every line they changed, how they got there, and how deep their skills go.
No credit card required | Quick 5 mins setup
Candidates assessed
Directly cuts down time-to-hire by
Technical skills covered
Candidate completion rate
Key outcomes
for tech and engineering teams
Shortlist you can trust, without reading every resume
Upload resumes in bulk. Each one is scored and sorted into strong and weak fit, so your team starts with the best profiles.
No screening the same profiles again and again
HR and hiring managers work from one list, with tags, comments and recommendations on each candidate.
Keep control of candidate communication
Selection and rejection emails are optional. Send them from the platform, or keep all communication on your own channel.
Send hiring managers candidates with proof of skill
All candidates complete a hands-on Task, so the panel sees real work before the interview.
Solve your top challenges with resume shortlisting
Resume shortlisting key challenges
Utkrusht solutions
Hundreds of applications for one role
Every resume is scored and ranked and given a best-fit score as soon as it is uploaded
The ATS score can't be trusted. A 59% profile is missing the skills, a 0% profile has them
Each shortlisted profile shows the evidence for every must-have skill, so the reason for the pick is clear
Every resume looks the same, with the same claims and the same numbers
Strong anti-proctoring feature set. Plus, candidates debug and fix a running system with AI allowed. The recording and prompt trail show who did the thinking
Shortlists travel by email and Excel, and feedback comes back late
One shared pipeline from invited to selected, with an Excel export when you need it
Good candidates get rejected on paper, and weak ones get through
Shortlisted candidates complete a Task, so skills are proven before interview time is spent
Features that
make Utkrusht different than others
Evaluation method
Resume fit score
Each must-have skill from your job description is marked as demonstrated or only listed, with the supporting line from the resume.
In-depth candidate profiling
Candidate deep research
GitHub profiles and any links the candidate shares are researched: how old the profile is, which projects are real work and which are learning exercises, and how deep the work goes.
High-volume
Bulk upload and search
Upload resumes in bulk, search the whole pipeline in plain language, and select or reject with your own email templates.
Candidate management
Tags, comments and a shared pipeline.
Tag candidates for manager review, filter by tag, and let hiring managers comment and recommend on the same page.
350+ Skills and Tasks
Tasks already built-in for screened and shortlisted candidates
Shortlisted candidates debug and fix a deployed system on their own machine. You get the recording and a report on skill, AI usage and problem solving.
FAQs
Can an HR team without a technical background use it?
Yes. The must-have skills are pulled from your job description, and the reason behind each score is written in plain language.
Does it work for non-technical roles?
It does, but it is specifically built for software and engineering roles. That focus is what lets it judge technical evidence in a resume.
Our ATS already gives a score. Why use another one?
Most ATS scores come from keyword matching. Utkrusht's score comes from real evidence and proof-of-work shown to you, and you can see the reason behind each skill.
Are low-scoring candidates rejected automatically?
No. A weak resume can still belong to a strong candidate, so selecting and rejecting is always your call.
Resumes are written to match the job description. How do you know the claims are true?
From the resume alone, you can't be sure. That is why shortlisted candidates take a Task and show the skill in a running system.
Still got questions?
Just book a call directly with our team
