AI Evaluation Engine
Scores candidates against structured criteria that adapt to role requirements, allowing different roles to use their own evaluation rubrics while maintaining consistent assessment across candidates.
How We Built a Hiring Platform That Cut Candidate Evaluation Time 72% With Structured AI Scoring, HRMS Sync, Candidate-Visible Feedback and Live Video Interviews
Recruiters were evaluating candidates through unstructured interviews, scoring them inconsistently, and losing days to scheduling and review. We built a platform that runs live video interviews with dynamic question sets, scores responses against structured criteria, and returns results to recruiters through a dashboard synced with HRMS. Candidates also get a transparent view of their own feedback.
Client Overview
An AI interview and candidate evaluation platform serving mid-market and enterprise organizations across North America and the European Union. The platform supports 15,000+ live video interviews, 45+ enterprise organizations, and 120,000+ candidate feedback records. It integrates with Workday, BambooHR, Greenhouse, and Lever through two-way REST APIs. Ciphernutz built the platform using Next.js, React, Node.js, NestJS, PostgreSQL, and OpenAI, with a dual recruiter and candidate portal.
Customer Quote
How long did it take your team to get from a completed interview to a comparable score before this?
Before this platform, a recruiter would finish an interview on Tuesday, spend an hour deciphering their own notes on Wednesday, and finally sync with the hiring manager on Thursday just to give a candidate a “maybe.” Now? The interview ends, the structured scoring rubric is instantly populated in Greenhouse, and the candidate gets actionable feedback in their portal before they even close their laptop. It turned a three-day manual bottleneck into a three-minute automated workflow.
The Challenge
Hiring decisions are high-stakes and often made from thin and inconsistent evidence. Different interviewers can assess the same candidate using different notes, standards, and conclusions, making candidate comparison difficult. Recruiters also spent significant time scheduling, conducting, and reviewing interviews. The platform needed to solve this while addressing AI evaluation fairness, reliable live video, HRMS integration, and the needs of both recruiters and candidates.
Unstructured Interviews Created Inconsistent Evaluation
Two interviewers assessing the same candidate could produce different notes, weigh different answers, and reach different conclusions because the interview process provided no common evaluation framework.
Manual Review Slowed the Hiring Funnel
Every interview required recruiter attention for scheduling, live participation, and post-interview review. Evaluation became the slowest step in the funnel, creating delays when strong candidates could be moving through other hiring processes.
AI Evaluation Required Fairness Safeguards
Automated candidate evaluation could systematically disadvantage candidates by language, background, or demographic characteristics if designed incorrectly. The evaluation engine therefore required deliberate model tuning, testing across varied candidate profiles, and explicit safeguards.
Live Video Had to Be Reliable
Video quality was a hard engineering requirement. A live interview that drops or degrades directly affects a candidate’s experience and cannot be treated like an ordinary recoverable application error.
HRMS Integration Had to Fit the Existing Workflow
A hiring platform that does not write evaluation data back into the HRMS creates a second system of record and forces recruiters to perform duplicate data entry.
Recruiters and Candidates Needed Different Experiences
Recruiters needed throughput, comparison, and evaluation visibility, while candidates needed clarity and transparency about a process that was assessing them.
The Solution / What We Built
We engineered a secure, dual-portal AI hiring platform that replaces unstructured interviews with standardized, rubric-based evaluation. The system combines live video interviews, automated Speech-to-Text transcription, role-specific AI scoring, HRMS synchronization, and candidate-visible feedback in one workflow.
Live Video Interview Module
Provides secure real-time video with dynamic question sets and automated recording for later review and defensibility.
Scoring and Feedback Dashboard
Gives recruiters immediate access to evaluation results, identified strengths, and performance analytics without reconstructing assessments from notes.
HRMS Integration Suite
Provides two-way synchronization with HRMS platforms so evaluation data flows into the existing system of record and recruitment workflow.
Privacy and Data Security Framework
Implements encrypted data handling and user privacy controls across interview sessions and recorded video data.
Dual Recruiter and Candidate Portals
Recruiters manage evaluations while candidates can view their own structured feedback and progress through a dedicated portal.
Results
Candidate evaluation time fell 72%, while interviewer productivity increased 81%. Structured scoring created uniform evaluation criteria across candidates, HRMS data moved automatically through two-way synchronization, and candidates gained real-time visibility into their own evaluation.
| Before | After | |
|---|---|---|
| Scoring Basis | Unstructured, per-interviewer | Structured criteria per role |
| Time to Comparable Result | Post-interview reconstruction | At interview completion |
| Candidate Comparison | Incompatible notes | Uniform scoring |
| Interview Recording | Rarely | Automated, reviewable |
| HRMS | Manual entry | Two-way sync |
| Candidate Feedback | Opaque | Visible in candidate portal |
How close would two interviewers score the same candidate?
We look at your hiring workflow and scope what makes it better.
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