An AI-Powered Interview & Candidate Evaluation Platform
AI Interviewer is an AI-powered interview platform designed to automate candidate interviews and evaluation. It supports both voice and text interviews, allowing organizations to conduct structured assessments without relying entirely on manual interview processes.
The platform uses AI-driven workflows and agents to generate dynamic interview questions and evaluate candidate responses across communication, problem-solving, and technical skills. Weighted evaluation criteria can be used to produce structured candidate scores and automated interview reports.
Expertizo developed the full-stack platform using Next.js, React, TypeScript, Node.js, ExpressJS, Firebase, and the OpenAI API. The implementation included reusable components, AI workflows, responsive interfaces, interactive dashboards, and Firebase integrations.
Manual Interviews Don't Scale With Hiring Volume
Traditional interview processes rely entirely on manual scheduling, live interviewer availability, and subjective, inconsistent evaluation criteria between candidates. As hiring volume grows, this becomes a bottleneck — interviewers spend hours on repetitive screening conversations, and candidates are assessed against different, often inconsistent standards depending on who conducts the interview.
Organizations needed a way to run structured, consistent interviews at scale, without sacrificing the depth of assessment across communication, technical skill, and problem-solving that a good interview process depends on.
What We Built
Key contributions from the Expertizo team
AI Interview Workflows
Built AI-powered workflows that support automated interviews, candidate interactions, evaluation, and assessment.
Dynamic Interview Questions
Implemented AI-driven interview flows that generate dynamic questions based on the interview and candidate context.
Voice & Text Interviews
Supported both voice and text-based interview experiences for flexible automated candidate assessments.
AI Candidate Scoring
Implemented automated evaluation across communication, problem-solving, and technical skills using weighted assessment criteria.
Automated Reports
Generated structured interview results, scores, and candidate reports to help organizations review assessments efficiently.
Interactive Dashboards
Built responsive interfaces, reusable React components, and interactive dashboards for managing interviews and reviewing candidate results.
Tech Stack
Technologies Used to Build AI Interviewer
Why Expertizo
What made this project possible
- Full-stack delivery — AI engine and user-facing application built by one team, no vendor handoffs
- Experience building AI agent workflows for dynamic, context-aware conversations
- Practical OpenAI API integration for real-time evaluation, not just chatbot wrappers
- Reusable component architecture designed for future feature expansion
Related Work
Other AI and automation platforms built by Expertizo
AI Interviewer Case Study FAQs
Common questions about this project
AI Interviewer is an AI-powered interview platform that conducts and evaluates candidate interviews through both voice and text interactions. It can generate dynamic interview questions, evaluate candidates across communication, technical skills, and problem-solving, and produce automated scores and interview reports.
The platform uses AI workflows to evaluate candidate responses against multiple criteria, including communication, problem-solving, and technical skills. Weighted evaluation criteria can be used to produce structured candidate scores and assessment results.
Yes. AI Interviewer supports both voice-based and text-based interviews, allowing organizations to conduct automated interviews through different interaction formats.
The platform was built using Next.js, React, TypeScript, Node.js, ExpressJS, Firebase, and the OpenAI API. Expertizo also developed AI agent workflows, reusable frontend components, interactive dashboards, and automated interview evaluation features.
Yes. Expertizo develops custom AI-powered recruitment and SaaS platforms, including AI agents, automated candidate evaluation, interview workflows, scoring systems, dashboards, and AI integrations.
Yes. The evaluation criteria and question flow can be tailored to different roles, so a technical role and a customer-facing role are assessed against relevant, weighted criteria rather than a one-size-fits-all rubric.
Yes. Automating the interview and initial evaluation step means hiring teams no longer need to conduct every screening conversation manually, freeing up time for later-stage, higher-judgment interview rounds.
Yes. Candidate data and interview records are stored using Firebase's secure infrastructure, with access controls designed around standard data protection practices for recruitment platforms.
Yes. The same AI agent, scoring, and dashboard architecture used for AI Interviewer can be adapted for other structured-evaluation use cases, such as candidate screening for training programs or customer intake assessments.
Have a Similar Project in Mind?
Tell us about it and we'll get back to you with next steps.