Interviewed (Indeed Assessments)
AI-driven talent assessments and automated candidate screening for high-volume hiring.
The World’s Most Advanced AI Interview Intelligence Platform for Data-Backed Hiring.
HireIntelligence is a high-performance interview intelligence platform engineered to eliminate the subjectivity and inefficiency of legacy recruitment workflows. By 2026, the platform has matured its multimodal AI architecture, which processes audio, video, and text inputs to generate deep psychometric and technical evaluations of candidates. Unlike standard video conferencing tools, HireIntelligence utilizes proprietary NLP models to map candidate responses against specific role competencies, providing recruiters with an objective 'Match Score.' Its market position is defined by its 'Interviewer Intelligence' module, which provides real-time coaching to hiring managers, ensuring every interview is compliant, consistent, and insightful. The platform integrates seamlessly into enterprise tech stacks via robust API hooks, enabling data-driven talent life cycle management. By leveraging predictive analytics, HireIntelligence doesn't just evaluate current fit; it forecasts long-term performance and cultural contribution, making it an essential utility for organizations scaling high-density technical and leadership teams.
Analyzes verbal content and sentiment to map candidate responses to the STAR (Situation, Task, Action, Result) method automatically.
AI-driven talent assessments and automated candidate screening for high-volume hiring.
AI-accelerated hiring that automates screening, scheduling, and candidate sourcing in one unified stack.
AI-Powered Technical Assessment and Video Interviewing Platform for Elite Talent Acquisition.
AI-driven talent assessment platform optimizing high-volume recruitment through skills-based intelligence.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses an anonymization layer to flag potential unconscious bias in interviewer notes and scores in real-time.
Machine learning model that correlates interview performance with historical 1-year retention data.
A low-latency overlay that suggests follow-up questions based on the candidate's previous answer.
Generates personalized, constructive feedback reports for unsuccessful candidates using generative AI.
Connects with internal Slack/Teams data to identify which current employees the candidate most resembles in skill profile.
Adjusts the difficulty and technical depth of subsequent questions based on the candidate's real-time accuracy.
The 1st-round screen for 500+ developers takes weeks.
Registry Updated:2/7/2026
Interviewer quality varies wildly across different regional offices.
Historical data shows a lack of diversity in final-round selections.