Screening + Shortlisting still feels like

"guesswork"

Screening + Shortlisting still feels like "guesswork"

Resumes lie, Phone-screens miss depth, AI tools quiz.

With AI, writing code is no longer a signal. HOW someone thinks, debugs live systems, makes tradeoffs, explains their approach, etc is.
No coding tests, no simulations, no artificial scenarios, Utkrusht is the only skill assessment platform to evaluate each candidate in actual deployed production environments, then shows you the Top 5-10 worth talking to

Resumes lie.
Phone screens miss depth.
Other AI tools quiz.

With AI, writing code is no longer a signal. HOW someone thinks, debugs live systems, makes tradeoffs, explains their approach, etc is.

No coding tests, no simulations, no artificial scenarios, Utkrusht is the only skill assessment platform to evaluate each candidate in actual deployed production environments, then shows the Top 5-10 worth talking to

Start for free

Start for free

No credit card required | Quick 5 mins setup
No credit card required
Quick 5 mins setup

Trusted by tech teams at small and mid-sized companies (typically <5000 employees)

Trusted by tech teams at small and mid-sized companies (typically <5000 employees)

The problem

6 most common screening + shortlisting methods used today, but teams still end up guessing and disappointed

Coding tests and challenges

Leetcode/Hackerrank-style mcqs, quizzes, proxy problems, easy to game, and no visibility into candidate's thinking process

Pair program/
Whiteboard tests

Artificial interview environment, highly interviewer-dependent, and time & resource intensive

Take-home assignments

Heavy review effort, leakable reusable assignments, and can only do with few candidates

ATS/CRM/Manual screening

Biased, time-consuming, filters by keywords (not skill), and always context switching

Phone screens/
Portfolio reviews

Fake profiles, subjective, inconsistent, tests talking not building skills, curated highlights not real production work

AI-based interview tools

Surface-level evaluation, no real work demonstrated, easy to script answers -- never accurately evaluates technical skills

6 most common screening + shortlisting methods used today, but teams still end up guessing and disappointed

Coding tests and challenges

Leetcode/Hackerrank-style mcqs, quizzes, proxy problems, easy to game, and no visibility into candidate's thinking process

Pair program/
Whiteboard tests

Artificial interview environment, highly interviewer-dependent, and time & resource intensive

Take-home assignments

Heavy review effort, leakable reusable assignments, and can only do with few candidates

ATS/CRM/Manual screening

Biased, time-consuming, filters by keywords (not skill), and always context switching

Phone screens/
Portfolio reviews

Fake profiles, subjective, inconsistent, tests talking not building skills, curated highlights not real production work

AI-based interview tools

Surface-level evaluation, no real work demonstrated, easy to script answers -- never accurately evaluates technical skills

Plus, no method today (especially with AI) shows you HOW a candidate thinks

— how they work, make decisions, tradeoffs, how they use AI, debug ambiguous problems, structure messy codes, maintain code hygiene, etc.

Plus, no method today (especially with AI) shows you HOW a candidate thinks

— how they work, make decisions, tradeoffs, how they use AI, debug ambiguous problems, structure messy codes, maintain code hygiene, etc.

Proven method that works

In the age of AI, Watch-them-Work assessments (compared to others) always gives you best candidates

In the age of AI, Watch-them-Work assessments (compared to others) always gives you best candidates

Our product

Why Utkrusht and what are "Watch-them-Work" Tasks to evaluate candidates?

Traditional screening/shortlisting methods and tools were built for a world where quiz scores predicted job performance.


That world no longer exists.


Today's developers and engineers ship with AI copilots, debug production systems, make real-time architectural tradeoffs, etc. — none of which show up in 30-question algorithmic coding challenges or take-homes.


Utkrusht was built from the ground up around one core belief: the only accurate way to evaluate tech candidates is to actually watch HOW they solve a real problem in a real environment, live.


In other words, simply watch-them-work.


1 task is an actual on-the-job task where candidates solve, debug, design, extend, refactor live apps, and deploy it in a live production environment.

We fundamentally believe in the age of AI, watching someone live solve real on-the-job production problems is the best way to accurately identify how good they really are.


In this process, allow them all the tools (including AI) of their choice and then become a fly on the wall!

for eg: For a -

  • Fullstack role, candidates are asked to debug and fix a broken API

  • SRE role, candidates are asked to write a runbook for incident response

  • AI Engineer role, candidates are asked to improve embeddings in a chatbot

  • Devops role, candidates are given a broken K8 cluster to fix, optimize a docker container, etc.

  • Data Engineer role, candidates are asked to fix kafka partitioning, optimize a hadoop cluster, etc.

  • Backend role, candidates are asked to live migrate a DB schema, refactor a payment microservice, etc.

  • and many more…



These tasks also allow you watch candidates how they debug, what decisions they made, what approach they follow, how they break down ambiguous problems, make tradeoffs, etc.


Tasks are designed to measure in-depth fundamental skills, use of AI, and problem-solving approach, making them actually build something live in-action and you watching their recorded session.


Know in 30mins whether this candidate is the best-fit for the job.
No more lengthy coding tests or take-homes that don't give good signals anymore.

Traditional screening/shortlisting methods and tools were built for a world where quiz scores predicted job performance.


That world no longer exists.


Today's developers and engineers ship with AI copilots, debug production systems, make real-time architectural tradeoffs, etc. — none of which show up in 30-question algorithmic coding challenges or take-homes.


Utkrusht was built from the ground up around one core belief: the only accurate way to evaluate tech candidates is to actually watch HOW they solve a real problem in a real environment, live.


In other words, simply watch-them-work.


1 task is an actual on-the-job task where candidates solve, debug, design, extend, refactor live apps, and deploy it in a live production environment.

We fundamentally believe in the age of AI, watching someone live solve real on-the-job production problems is the best way to accurately identify how good they really are.


In this process, allow them all the tools (including AI) of their choice and then become a fly on the wall!

for eg: For a -

  • Fullstack role, candidates are asked to debug and fix a broken API

  • SRE role, candidates are asked to write a runbook for incident response

  • AI Engineer role, candidates are asked to improve embeddings in a chatbot

  • Devops role, candidates are given a broken K8 cluster to fix, optimize a docker container, etc.

  • Data Engineer role, candidates are asked to fix kafka partitioning, optimize a hadoop cluster, etc.

  • Backend role, candidates are asked to live migrate a DB schema, refactor a payment microservice, etc.

  • and many more…



These tasks also allow you watch candidates how they debug, what decisions they made, what approach they follow, how they break down ambiguous problems, make tradeoffs, etc.


Tasks are designed to measure in-depth fundamental skills, use of AI, and problem-solving approach, making them actually build something live in-action and you watching their recorded session.


Know in 30mins whether this candidate is the best-fit for the job.

No more lengthy coding tests or take-homes that don't give good signals anymore.

How it works

Just 4 steps from a job role to a ranked shortlist of only the best candidates

01
Step 1 of 4

Create a position

Your JD → a live task, in minutes.

Create a position / list your hiring details / upload a JD

Or just select from the pre-built library of customisable job templates we have. We read through your job description, match relevant skills and prepare assessments. Later you'll get to invite candidates.

Upload a JD or paste a link — we extract the role automatically
Choose from a library of pre-built, customisable job templates
No manual skill-tagging — our AI matches the right signals
How we evaluate candidates

We don't create artificial scenarios or simulations. Instead, candidates are made to execute problems in a LIVE production environment.


Our platform then evaluates HOW someone thinks, approaches problems, makes tradeoffs, debugs a messy codebase, works on constraints, etc.

We're not an "AI-interview platform", instead we make them do real work exactly like they would on the job.


Usage of AI and recommendation metrics is also calculated. We even track if someone cheats, or other methods of unfair practices by proctoring the sessions.

Within 30mins, you get detailed analysis (+ video session recordings) of all candidates with their scores evaluated on different signals


Candidates are ranked based on objective rubrics across technical execution, AI usage, communication, through process, judgement, problem-solving, etc.

Compare "Strongly recommended to hire" vs "not recommended to hire" summary on your dashboard (our customers LOVE our candidate reports, request one to see a sample)


Our rigorous research and back-testing (12k+ candidates assessed) has proved these 5-10 candidates are your strongest quality candidates

Spend your valuable time talking to only 5-10 best candidates

(no more wasting time on constant interview loops)

Top 5 features our customers love

Actual tasks

Watch candidates solve on-the-job tasks before you even speak to them.

These tasks are not any simulations or scenarios, instead they're rigorously tested and designed to make candidates work in live production environments.

Actual real production environment

Candidate rubrics

Insights gathered from resume, candidate responses, public socials, etc.

e.g. Intent to join, location match, salary alignment, culture fit, etc.

Candidate Rubrics

Lowest drop-off rate

Since our assessments are quick 30mins, candidates LOVE taking it.

Not on weekends or after-office, but 70% of our assessments are taken in middle of the day, during breaks, etc.

So you can be rest assured almost all candidates you send the assessments to, will complete it (and love to take it).

AI is allowed, cheating is caught

Candidates are allowed to use AI and other tools available to them.

Since our platform video-records the session, we show you exact insights on how they used AI, where, how much, was it helpful or just copy-pasted, etc.

Basically, we show you HOW candidates used AI.

SmartRank

SmartRank

Put a simple query with your specific/niche criteria you might have, to get those calibre candidates too


e.g. "I want to see candidates who have worked for startups previously", "I want to see candidates who have experience in BFSI sector too".


Candidates assessed

18000+

Directly cuts down time-to-hire by

750%

Technical skills covered

11500+

Candidate completion rate

0%

  • "Utkrusht has been pivotal for us. Their assessment tests help us find the candidates with required technical skills and their detailed analysis improved our time spent on interviewing candidates significantly. We now realise how much time we used to waste on screening"

    Jaydeep Roman

    VP of Products, Wybrid

  • "Relying solely on recruiter agencies not only took 2-3 months on average, but we still ended up interviewing candidates who couldn't deliver desired code. With Utkrusht, we shortlisted 3 strong candidates in just a week, and every single one of them could build robust code!"

    Harshal Bhakta

    Co-founder, Cital

  • “We’ve hired developers who looked great on paper but collapsed in real projects. Utkrusht's platform changed that. Now we don’t guess, we see how they code and work under real conditions. The quality of our hires has gone way up, and we’re no longer wasting time on interviews that go nowhere.”

    Atul

    Co-founder & COO, ScaleReal

  • "AI-based assessments have helped us speed up our recruitment process while improving the quality of hiring.

    The detailed technical evaluations make it easier to make quick and confident decisions. What really stands out is the team’s personalized support, quick response. Overall, it has been a great experience working with this innovative tool and the amazing people at Utkrusht."

    Arun Bhimani

    VP of Technology, InTech Solutions

  • "We evaluated at least 15 other skill assessment tools which are out there. They are good, but they test candidates on algorithm questions and theory knowledge. None showed us how someone would actually perform on our team. With Utkrusht, I watched candidates work through the same debugging and optimization problems my engineers face daily. That's when I knew who to hire."

    Husna Kouser

    Director of HR, Skills Agency

  • "We were spending 15 hours a week screening resumes and doing first-round calls. Most candidates couldn't even explain their own projects and things they wrote on their resume.. Utkrusht's 20-minute real-job simulation assessments cut through that. We now just know before interviewing candidates they have shown strong technical skills."

    Vedang Manerikar

    Founder, Unravel Tech

  • "My senior developers were spending 20+ hours a week doing code pairing sessions and reviewing take-home assignments. With Utkrusht, All candidates complete the same “build something” assessment, the platform stack ranks them automatically, and I get a clear top 10. So we now only interview candidates who've already shown clear proof-of-skill."

    Tanay Shah

    Founder, Pardy Panda Studios

FAQs

Why Utkrusht?

Evaluation

Hiring Process

What is Utkrusht and when do I use your platform in my hiring?

Isn't this another AI video interview platform? How is Utkrusht different from other screening or skill assessment platforms?

How is this different from HackerRank or CodeSignal or others?

Is there any refund policy if I'm not happy with using the product?

We already have a process in place/We haven't used any product for this before

How do I get started?

Is this for startups or larger companies

What do candidates think about this?

FAQs

What is Utkrusht and when do I use your platform in my hiring?

Isn't this another AI video interview platform? How is Utkrusht different from other screening or skill assessment platforms?

How is this different from HackerRank or CodeSignal or others?

Is there any refund policy if I'm not happy with using the product?

We already have a process in place/We haven't used any product for this before

How do I get started?

Is this for startups or larger companies

What do candidates think about this?

Why Utkrusht?

Evaluation

Hiring Process

You scrolled to the bottom of this page, and still not sure if this is right for you?

what's the worst case scenario to try out once?

You scrolled to the bottom of this page, and still not sure if this is right for you?

what's the worst case scenario to try out once?

Still got questions?

Still got questions?

Just book a call directly with our team

Just book a call directly with our team