What Feenyx Uses to Assess Candidates—and What Its AI Does

Feenyx uses skills assessments, asynchronous and live interviews, resume analysis, AI-assisted evaluation and authenticity checks, according to its public product descriptions. It does not rely on one universal assessment method: coding tests, written responses and interview evidence are evaluated differently.

Recruiter.com announced that it completed its acquisition of Feenyx on August 31, 2026. Its acquisition announcement describes that combination of tools. The useful distinction for candidates is what produces a score, what helps an interviewer review evidence, and what merely raises an alert. The product descriptions below were checked on October 7, 2026.

What Feenyx evaluates

Coding: test results and performance measures

For coding assessments, Feenyx says it runs candidates’ code against test cases and compares the output with the expected result to determine whether each case passes or fails. It also rates coding time, execution time, memory usage and code quality. Employers receive a leaderboard of candidates and their scores. These are documented scoring inputs—not just an AI summary of a conversation. Source: Feenyx coding assessments.

For preparation, practice solving relevant problems, checking edge cases and testing your solution. Ask the recruiter which language, environment and resources are permitted; do not assume a general practice test matches the employer’s assessment.

Writing: an employer-defined rubric

Feenyx’s AI-scored writing assessments evaluate responses against a customizable rubric. Employers can choose criteria such as clarity, correctness, style, technical depth or brand alignment and assign weights to them. Examples include technical explanations, documentation, customer communications and product requirement documents. Source: Feenyx writing assessments.

That means a writing score depends partly on the employer’s criteria and priorities. Ask what the task is intended to measure, and write for its stated audience and purpose rather than trying to satisfy an imagined generic “AI preference.”

Resumes and interviews: extracted skills and collected evidence

Feenyx’s AI disclosure describes several supporting functions:

• Natural language processing extracts skills from resumes and job descriptions and generates video transcripts.
• Generative AI summarizes transcripts for faster review.
• Generative AI compares collected evidence with required skills and suggests interview questions to address gaps.

For example, if a role requires a skill that an applicant’s evidence has not demonstrated, the described workflow can suggest a follow-up question about it. The interviewer may choose whether to use that question.

The disclosure says those suggested questions do not contribute to candidate ranking or automatic processing. It does not say that every Feenyx feature is unscored. The homepage separately advertises resume comparison and scoring, as well as interview analysis, transcription and scoring. These public descriptions do not provide a complete formula showing how all those outputs combine for a particular vacancy.

What webcam and authenticity checks mean

Feenyx says it uses computer vision for webcam proctoring during assessments. Its disclosure distinguishes face detection—whether a face is detectable—from facial recognition, which would identify a specific person. Face-detection alerts do not automatically disqualify candidates and must be reviewed by a hiring manager. Source: Feenyx AI disclosure.

Separately, its homepage advertises flags for suspicious activity, hidden helpers and AI-generated answers. Those are vendor claims about detection capabilities, not proof that a flag establishes misconduct. Nor does the face-detection description establish that facial expressions or emotions determine a candidate’s score.

Before starting, confirm whether AI assistants, notes, external websites or another monitor are allowed. If camera access, speech transcription or another part of the format creates a barrier, ask the employer for an alternative or review process; our AI video interview accommodations guide explains practical requests.

What candidates and HR should confirm

Ask the hiring team:

1. Which modules are enabled? A coding test, writing task and recorded interview generate different evidence.
2. What is scored? Request the criteria, weights where available, and whether a cutoff or ranking affects progression.
3. Who reviews errors or alerts? Confirm how to challenge an inaccurate transcript, skill extraction or authenticity flag.

For HR teams, also check whether scores measure the actual job requirements and whether reviewers can inspect the underlying work. Feenyx’s writing assessment page claims its AI scoring eliminates human bias, but a product claim is not independent evidence of fair selection outcomes. A configurable rubric still needs scrutiny before its scores guide hiring decisions.