Utkrusht AI

The main 6-8 tech candidate assessment/evaluation methods today are either flawed, weak, or ineffective as they do not mirror or replicate the actual conditions of the job, so there’s no way to evaluate HOW a person thinks.. Even with using these methods today, tech teams still have all sorts of pain points as mentioned below in this document. And especially now with AI, writing code is no longer a strong signal to accurately evaluate a candidate. So our product Utkrusht does assessments that actually shows HOW a candidate works and behaves in real job situations. We’re the first platform to provide a new assessment method – “Watch-them-Work” style assessment tasks, which covers 3 main points – Candidates actually do live deployments in a production environment It shows HOW a candidate thinks – makes judgements, how they use AI, can they explain their choices, ask about constraints, can they walk you through examples, etc.… And saves you time, cost, resources on shortlisting and

Utkrusht is a technical assessment platform designed to accurately evaluate candidates by observing their problem-solving skills in real deployed production environments. Instead of traditional methods that often lead to guesswork, it focuses on how candidates think and work in real scenarios, providing a shortlist of the top candidates worth interviewing. It combines rigorous assessments with AI integration to improve the hiring process. Users can create a position by uploading a job description, which the platform uses to generate relevant tasks. Candidates then solve these tasks in a live production environment, allowing evaluators to see how they approach problems and make decisions. After the assessment, users receive detailed reports with rankings and insights into each candidate's performance, including their use of AI and communication skills. Utkrusht is aimed at small to mid-sized tech teams looking to enhance their hiring processes without the inefficiencies of traditional methods. It is particularly beneficial for organizations that want to assess candidates' actual coding capabilities in realistic environments and reduce the time spent on ineffective screening methods.