There are about 8 methods to screen + shortlist tech candidates today -- coding tests, take-home assignments, DSAs, pair-programming, AI-interview tools, etc. The obvious ones.

Still, tech leaders (at custom development companies, small engg teams, etc.) have all sorts of problems -- 

- spend 1/3rd of time on hiring activities
- time from job-to-hire is still 4-6 weeks on average
- hire people who look good on profile, yet fail on the job
- no way to identify how a person thinks and works -- thought process, makes judgements, how they use AI, can they explain their choices/trade-offs, ask about constraints, can they walkthrough examples, etc.

Our product Utkrusht introduces a new (and first) “watch-them-work” assessment method where -

- candidates solve, debug, and deploy real engg on-the-job tasks in live production environments, 
- you also see HOW they actually think, decide, debug, solve problems end-to-end, and build stuff, live in action (use AI if they want) -- not just what they claim on resumes or say in interviews

This accuracy, depth, and structured thought process of their approach to solve these tasks identifies your Top 5-10 out of 100s of resumes you could have.

Result: you hire strong candidate in less than 7 days, in 1/10th of your current cost, and spend like 1 hour of your/ team's time -- every single time.

Let us show you a quick demo how it works?

Utkrusht AI

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Utkrusht AI

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