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Karat

Karat is an AI-powered HR & Recruiting tool — AI technical interviews with expert interviewers. Best for: Code Generation & Code Review. Pricing: Paid (GateOnAI Score: 47/100).

AI technical interviews with expert interviewers

PaidVerifiedCode GenerationCode ReviewDebuggingJob SearchRecruitingInterview PrepHR AutomationAI AssistantAI AgentLarge Language Model

Conduct technical interviews through a hybrid AI and human system that records, evaluates, and scores candidates in real time. The platform auto‑schedules sessions using calendar integration, eliminating back‑and‑forth emails. Candidates code in a browser‑based IDE that captures keystrokes, test results, and execution time. An AI layer parses solutions, flags inefficiencies, and generates a preliminary difficulty rating before the expert interviewer joins. Live video connects the candidate with a vetted engineer who can probe deeper, while the AI logs every question and response for later review. Recruiters, engineering managers, and talent acquisition teams use Karat to replace phone screens and ad‑hoc coding challenges. The dashboard aggregates scores, AI‑derived skill tags, and interviewer notes into a single view, enabling data‑driven shortlisting. Integration with Applicant Tracking Systems such as Greenhouse and Lever syncs candidate profiles automatically. Comparative analytics highlight trends across hires, revealing potential bias and helping refine job descriptions. Companies report a 30 % reduction in time‑to‑offer because the AI pre‑screen eliminates low‑performing applicants before human review. Pricing is available only through an enterprise‑level subscription, with tiers based on interview volume and support options. The model includes unlimited interview minutes, dedicated account management, and API access for custom workflow automation. Because the service relies on live expert interviewers, scheduling can be impacted by time‑zone constraints, and the subscription cost may be prohibitive for early‑stage startups. Nonetheless, organizations seeking consistent technical evaluation at scale find the blend of AI insight and human judgment a practical alternative to fragmented interview pipelines.

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