Utkrusht AI shipped an AI-Ops screen that evaluates how candidates handle asynchronous agent queue failures.

There are mainly 6-8 methods today to evaluate tech candidates -- phone screens, tech interviews, coding tests, take-homes, pair-programming, AI-interview tools, etc. -- the obvious ones. Still, engg/recruitment teams at small and mid-sized companies have all sorts of problems - - spend 30% of time on hiring activities - shortlist-to-interview candidate quality is poor - 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 -- makes judgements, how they use AI, can they explain their choices/trade-offs, ask about constraints, walkthrough examples, etc. So, after reviewing 100+ tools and methods and taking our lived experience from Oracle and Microsoft, we built Utkrusht AI, that introduced 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, build stuff, solve problems end-to-end, live in action (use AI if they want) -- not just what they claim on resumes This accuracy, depth, and structured thought process of their approach to solve these tasks identifies your Top 5-10 out of 100s of candidates you have. Result: you hire strong candidates in less than 7 days, in 1/10th of your current costs, and spend like 1 hour of your/ team's time -- every single time. Want to see how "Watch-them-Work" Tasks look like? Send us a DM, and we can send you sample Tasks.

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