Sherlock AI is the closest tool to Trueyy on this list. Both are built specifically to catch AI-assisted cheating in live remote interviews, both run alongside your Zoom, Meet, and Teams calls, and both name the same threats — Cluely, Interview Coder, and the rest. The difference is architectural, and it is the thing to understand before you choose: where each tool actually looks.
This is an honest comparison between two tools in the same category. They make different, defensible design choices. Which one fits depends on what your team values.
What Sherlock AI is built for
Sherlock is a live-interview integrity tool that works as a meeting-side agent. You connect your calendar, toggle it on for an interview, and it joins the call — with, per Sherlock, no software for the candidate to install. According to its own materials, it analyzes behavioral and audio signals — response timing and pacing, answer structure and phrasing, and voice patterns — to model natural versus AI-assisted interaction, and it also targets deepfakes and impersonation.
Sherlock positions this as a privacy-forward approach. In its writing on the subject, it says it does not read the candidate's screen, webcam, or keystrokes, and instead works from behavioral patterns. It integrates with applicant tracking systems and, on higher tiers, adds AI-fluency scoring and note-taking.
That is a genuinely appealing model for teams that want the lightest possible footprint: nothing on the candidate's machine, and a stated commitment not to watch the screen or keyboard.
The core difference: inferred behavior vs device signals
Here is the honest axis between the two tools.
Sherlock infers from the outside. It reasons about timing, phrasing, and audio to decide whether a candidate is likely being assisted, without touching the candidate's device. That is low-friction and privacy-forward. The tradeoff is inherent to inference: a slow, unusually structured, or highly articulate answer can resemble assistance, and a real overlay leaves its clearest evidence on the device itself — in the apps running and the paste patterns — rather than in the cadence of speech.
Trueyy reads the device, with consent. It reads device-level signals on the candidate's machine — apps and screen activity, keystroke and paste patterns, and voice — and recognizes 50-plus tools by the structure of their output. That is more direct evidence of what is actually running during the call, at the cost of a lightweight, consented presence on the machine rather than none at all.
Neither choice is simply "right." A team that prioritizes zero candidate footprint above all may prefer the meeting-side approach. A team that wants device-level evidence of the specific tool in use will prefer Trueyy. What matters is knowing which one you are buying, and not mistaking one for the other.
What Trueyy is built for
Trueyy sits beside your Zoom, Meet, or Teams call and reads device-level signals on the candidate's computer in real time, with their consent, no browser lockdown and no heavy install. It scores risk about every 30 seconds across three surfaces — apps and screen activity, keystroke and paste patterns, and voice — and recognizes ChatGPT, Claude, Gemini, Copilot, Cluely, Interview Coder, and 50-plus tools by the structure of what they produce, not a keyword blocklist. (Reading-gaze detection is on the roadmap, not live yet.)
No video is recorded or stored on Trueyy servers; audio is transcribed and screenshots are encrypted and retained per policy. There is no biometric identification, and a human always makes the final call. The output is a risk timeline you review, not a verdict the software hands down.
Capability comparison
| Sherlock AI | Trueyy | |
|---|---|---|
| Category | Live-interview AI-cheating detection | Live-interview AI-cheating detection |
| Approach | Meeting-side agent joins the call | Reads device-level signals beside the call |
| Candidate install | Per Sherlock, none | Lightweight, consent-based |
| Primary signals | Timing, phrasing, voice; deepfake / impersonation | Apps / screen, keystroke / paste, voice |
| Reads the device / screen | Per Sherlock, no | Yes, with consent |
| Names tools (Cluely, Interview Coder) | Yes | Yes, 50+ by output structure |
| Real-time | Yes | Yes, risk scored ~30s |
| Evidence style | Inferred from behavior and audio | Direct device signals |
| Video stored | — | No video stored on servers |
(Sherlock's product details above reflect its own public materials; some specifics vary across its site and third-party listings, so verify current behavior directly with the vendor.)
Which tool wins which job
- Choose Sherlock AI if a zero-footprint, privacy-forward, behavioral approach is your priority and you are comfortable with detection that infers assistance from timing, phrasing, and audio.
- Choose Trueyy if you want device-level evidence of the actual tool in use — apps, screen activity, and paste patterns — gathered with the candidate's consent, beside the calls you already run.
Both belong to the same young category, and both are reasonable answers to the same problem. For the wider set of shapes this comes in — exam proctors, coding assessments, and AI-run interviews — see Trueyy vs Proctorio, Trueyy vs HackerRank, and Trueyy vs Fabric.
A word on fairness and accuracy claims
Every vendor in this category, ourselves included, should show its work. The backdrop is real enough — 22% of job seekers report using AI during live interviews and a Checkr survey of 3,000 managers found 59% suspect candidates misrepresent themselves with AI — but that urgency is exactly why unvalidated accuracy claims deserve scrutiny. Be skeptical of headline accuracy numbers that arrive without a published methodology or an independent benchmark — there is no neutral, third-party test of interview-cheating detection yet, so treat all self-reported figures as directional. And never act on a single flag. Weigh multiple signals, disclose monitoring, get consent, and keep a human in the final decision. That discipline matters more than any one tool's marketing.
Frequently asked questions
Is Sherlock AI a Trueyy alternative?
Yes — they are in the same category: live-interview AI-cheating detection alongside your video calls. They differ in approach. Sherlock joins the meeting and infers assistance from behavioral and audio signals without touching the device; Trueyy reads device-level signals on the candidate's machine, with consent. Which fits depends on whether you value zero candidate footprint or direct device evidence.
What is the main difference between Sherlock and Trueyy?
Where each one looks. Sherlock, per its materials, does not read the screen or keystrokes and instead infers cheating from timing, phrasing, and voice. Trueyy reads device-level signals — apps and screen activity, keystroke and paste patterns, voice — with the candidate's consent, for more direct evidence of the specific tool in use.
Does Sherlock require the candidate to install anything?
Per Sherlock's own description, no — it works as a meeting-side agent that joins the call. That zero-install model is one of its main selling points. Trueyy uses a lightweight, consent-based presence on the machine to read device signals directly.
Does Trueyy read the candidate's screen?
Trueyy reads device-level signals — apps and screen activity, keystroke and paste patterns, and voice — with the candidate's consent. It does not record or store video on its servers, uses no biometric identification, and keeps a human in the final decision.
Which one is more accurate?
There is no independent, third-party benchmark for interview-cheating detection, so any accuracy claim — from Sherlock, from us, or from anyone else — is self-reported and should be read as directional. The more useful questions are what kind of evidence each tool produces (inferred behavior vs device signals), how it handles false positives, and whether it keeps a human in the decision.
Sherlock AI and Trueyy are two honest answers to the same new problem, built on different bets about where to look. If you want to see what device-level signal reading looks like beside your existing calls, book a demo and judge the evidence for yourself.