Short answer: yes, and Woven is the platform in this series most likely to actually catch you, because it does not rely on software to do it. Woven's position is that "algorithmic detection doesn't work". Instead, a human engineer watches a playback of your submission and judges whether the work looks like yours. Two certified engineers already score every Woven assessment against a rubric, so AI detection is one more line item for people who are reading your session anyway.
Last checked: September 17, 2026. Every proctoring claim below links to Woven's own published material. We build InterviewMan, an AI interview assistant, so read the practical advice with that in mind.
Key takeaways:
- Woven describes itself as the only technical assessment with remote proctoring on every plan, and its detection method is human review rather than a classifier (woventeams.com).
- "Skilled human experts" review every assessment for signs of external assistance, watching "a live playback of the candidate's submission" against defined guidelines.
- Woven's published figures: "1 in 10 developers cheat on their tech assessment or take-home exercise" with a tool like Claude, Cursor or ChatGPT, and unproctored candidates who do so are "3 times more likely to advance to the next round".
- Every submission is scored by two Certified Engineers against a detailed rubric (woventeams.com).
- The assessments are 90 to 120 minute real-work scenarios: reviewing a GitHub pull request, systems design, debugging. Not algorithm puzzles.
- Woven does not publish a webcam proctor, a lockdown browser or a process scan. The playback of your work is the evidence.
What Woven is
Woven sells human-powered technical skills assessments, aimed mostly at experienced developers rather than new graduates. Its whole positioning is a rejection of automated screening: it argues that a machine-graded algorithm puzzle tells you very little about whether someone can do the job.
The format follows from that. Woven's assessments run "from 90 to 120 minutes for candidates" and use scenarios drawn from real engineering work, including "Github Pull Request Review and Systems Design/Debugging". You are not asked to invert a binary tree. You are asked to review someone else's pull request and say what is wrong with it, or to debug a system that is behaving badly, and to explain your reasoning as you go.
Then it is graded by people. Each submission is "reviewed and scored by experienced engineers, offering a personalized and nuanced evaluation", with results delivered within one day. Woven says every submission is reviewed by two Certified Engineers scoring against "an obsessively detailed rubric", and that scorers get "ongoing coaching for new scenarios, languages or changes to rubrics".
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Try InterviewMan FreeThe candidate-facing framing in Woven's getting started guide is that the work is "real engineering work you might encounter in this role, not some automated academic computer science problem", and that "your future team went through this work simulation under the same timebox and conditions".
What Woven monitors
The playback of your session
This is the core of it. Woven records your work and a human watches it back. The company's async proctoring page describes reviewers watching "a live playback of the candidate's submission" and evaluating "their behavior and final responses against defined guidelines".
Woven does not publish exactly what the playback captures, and we will not pretend otherwise. It clearly includes the text and code you produce over time, because that is what makes a playback meaningful. Whether it extends to screen capture beyond the assessment surface is not documented.
Human proctoring on every plan
Most platforms in this category gate their strongest integrity features behind an enterprise tier. CoderPad's webcam proctoring is Enterprise-only, for example. Woven's claim is the opposite: remote proctoring on all plans. If you are taking a Woven assessment, assume a person will review it, because that is the default product rather than an upsell.
Your written reasoning
Woven scenarios ask you to explain, not just to produce. A pull request review is mostly prose. This matters enormously for detection, because model-written technical prose has a texture that engineers reading dozens of these develop an ear for: comprehensive, balanced, structurally identical from candidate to candidate, and oddly reluctant to commit to a recommendation.
Timing inside the timebox
The scenario is timeboxed, and the reviewer sees how the time was spent. A candidate who produces nothing for twenty minutes and then produces a complete, well-organised review in four is telling a story without meaning to.
What is not on the list
Woven publishes no webcam proctoring product, no tab-switch log, no clipboard log, no browser extension detector and no automated code-similarity engine. Its explicit argument is that algorithmic detection catches only "lowest-effort usage of AI", which is why it spends money on people instead.
What Woven cannot see
| Signal | Woven sees it | Notes |
|---|---|---|
| Your work as it develops over time | Yes | Playback reviewed by a human |
| Your written reasoning and its style | Yes | The main graded artefact on many scenarios |
| Pacing inside the timebox | Yes | Visible in the playback |
| Whether your explanation matches your code | Yes, by human judgement | The strongest signal on this platform |
| Tab switching | Not documented | No published tab log |
| Copy and paste events | Not documented | A paste is still visible in a playback as a sudden block |
| Webcam feed | Not documented | No published webcam proctoring product |
| Applications running on your desktop | No | No desktop agent published |
| A phone or second screen beside you | No | Nothing published watches the room |
| Your network traffic | No | Woven does not sit on your network |
Read that table carefully, because it is easy to misread. Woven has the fewest documented telemetry signals of any platform in this series and the highest realistic chance of catching AI use. Those two facts are not in tension. A human watching a replay does not need a clipboard log to notice that forty lines of polished prose appeared at once.
How Woven scores or flags suspicious behavior
There is no suspicion score. AI detection is folded into the same rubric-driven review that produces your grade. In Woven's framing, it is "one more rubric item" for engineers who are already reading your submission line by line.
The published numbers behind this are worth quoting exactly, because they explain the investment:
- "1 in 10 developers cheat on their tech assessment or take-home exercise" with a tool like Claude, Cursor or ChatGPT.
- Candidates using those tools without proctoring are "3 times more likely to advance to the next round".
- Which means, in Woven's arithmetic, "1 in 3 of tech interviews are with someone who cheated" for hiring managers not using proctoring.
Those are vendor figures from a company selling proctoring, so weigh them accordingly. The direction is consistent with what other platforms report, and the third figure is a derivation rather than a measurement.
Woven also makes an honest distinction that most vendors skip: reviewers must separate acceptable practice, such as consulting Stack Overflow, from actual cheating where the skill being measured was never exercised. That line is a judgement call, and Woven says so rather than pretending a threshold exists.
What recruiters see in the report
A Woven report is an evaluation document, not an integrity dashboard. The hiring team gets:
- rubric scores across the dimensions the scenario was built to measure
- written commentary from two certified engineers explaining each score
- an assessment of whether your work showed signs of external assistance
- your actual submission: the code, the review comments, the design reasoning
- results turned around within about a day
There is no red flag icon and no percentage. If the reviewers doubted the work, that doubt arrives as a sentence written by an engineer, which is considerably harder to dismiss than an automated flag. Hiring managers tend to treat "two engineers independently thought this looked AI-assisted" as close to decisive.
Using an AI interview assistant on Woven: what works, what is risky
The policy question comes first. If the employer's instructions prohibit outside assistance, using an AI assistant breaks them and a withdrawn offer is a real outcome. Woven's whole product exists because employers want that instruction enforced, so this is not a platform where the rule is ambiguous. Read Should you use AI in a job interview in 2026? and which companies allow or ban AI in interviews before you decide anything.
We are going to be more direct here than on any other platform in this series.
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Try InterviewMan FreeWoven is the worst place to lean on a tool that writes for you. Not because the software will catch you. Because two engineers will read the output and one of them will say "this reads like a model". The scenarios are prose-heavy by design, the reviewers are trained on exactly this, and the review is the product rather than a bolt-on.
Specifically risky:
- Pasting model-written pull request comments. This is the highest-signal failure mode on the platform. Model review comments are thorough, polite, evenly weighted across every file, and never say "this whole approach is wrong, here is why". Human reviewers do say that.
- A playback with no drafting. Text that appears in finished blocks reads as pasted whether or not any log confirms it.
- Design reasoning you cannot defend. Woven scenarios are chosen because they have arguable answers. Handing in an argument you did not build leaves you with nothing to say when asked about it.
What is technically outside Woven's documented surfaces:
Woven publishes no browser telemetry, so extension detection and clipboard logging are not the risk here. If you use a tool at all, a native desktop application avoids the surfaces that exist elsewhere. Our AI interview assistant is built that way: on macOS and Windows the overlay is excluded from screen capture and recording APIs and hidden from the dock, taskbar and app switcher, and the two-device Stealth Mode moves the answer display to a phone or second browser.
We list what each mode covers, and what it does not, on our undetectability page. InterviewMan does not type or submit for you, does not execute code, and does not hide network traffic, so whatever ends up in the playback is what you actually typed.
Where a tool genuinely helps on this format:
Preparation. Woven scenarios reward a specific skill that most candidates never practise: reading unfamiliar code critically and articulating what is wrong with it. Working through pull request reviews out loud with an assistant, before the assessment, builds that. That is the case for AI mock interview practice, and on Woven it is the use that actually moves your score.
For reference, our pricing is a free trial with no credit card, then $30 per month or $12 per month on the annual plan at $144 a year, with stealth features on every plan. Apps are on the download page.
How to prepare for a Woven assessment honestly
- Read Woven's own candidate guidance. The getting started article and the rest of the help center set expectations about the timebox and the format.
- Practise reviewing code you did not write. Pick open pull requests in a project you use and write a real review. This is the single highest-return preparation for a Woven scenario.
- Practise debugging under a clock. Systems debugging scenarios reward a methodical narrowing process, and the reviewer is scoring the process, not only the fix.
- Write the way you talk. Reviewers reward a clear, opinionated voice. It also happens to be the thing that reads least like a model.
- Do not aim for complete. A 90 to 120 minute scenario is designed so most people do not finish. Prioritising well is part of the rubric.
- Do the fundamentals. Our interview prep hub, the technical interview preparation guide and how to pass a coding interview in 10 steps cover the wider preparation.
How Woven compares to CodeSignal, HackerRank, CoderPad, and Codility
| Platform | Detection approach | Webcam proctoring | Tab and paste logging | Human review of every submission | Turnaround |
|---|---|---|---|---|---|
| Woven | Human proctoring on all plans, no algorithmic classifier | Not documented | Not documented | Yes, two certified engineers | About one day |
| CodeSignal | Numeric Suspicion Score from telemetry and similarity | Yes, on proctored assessments | Yes | No, automated first | Immediate score |
| HackerRank | ML plagiarism model plus MOSS structural matching | Optional | Yes | No, automated first | Immediate score |
| CoderPad | Playback plus behavioural review, no named classifier | Enterprise plans only | Yes, in Screen | Depends on employer | Varies |
| Codility | Similarity Check across past submissions, plus AI detection | Optional | Yes | No, automated first | Immediate score |
Sources: HackerRank on plagiarism detection, CodeSignal on Suspicion Score, Codility on plagiarism prevention and fraud detection, CoderPad's cheating prevention documentation.
Woven's honest advantage over the automated platforms is that it produces very few false accusations. A classifier can flag a strong candidate for writing clean code. Two engineers reading a submission rarely make that mistake. Its honest disadvantage is cost and scale: human review does not run at ten thousand candidates a week, which is exactly why the automated platforms exist. We cover that trade-off across the industry in how companies detect AI cheating in interviews.
Frequently asked questions
Does Woven detect ChatGPT?
Yes, that is an explicit product feature, but not through a classifier. Woven's approach is human: reviewers watch a playback of your submission and judge it against defined guidelines, as one item in the same rubric that produces your score. The company argues directly that algorithmic detection catches only the lowest-effort AI use.
Is every Woven assessment proctored?
Woven says it is the only technical assessment with remote proctoring on all plans, so proctoring is the default rather than a paid upgrade. That is different from most competitors, where the strongest integrity features sit behind enterprise pricing. Assume a person will review your session.
Does Woven use a webcam?
No webcam proctoring product appears in Woven's published material. Its proctoring is asynchronous review of your work rather than live observation of you. That means nothing published watches your room, your desk or your eyes.
Does Woven track tab switching or copy and paste?
Neither is documented as a logged signal. But a paste is still visible in a playback: a block of finished text appearing at once looks like exactly what it is. On this platform the playback substitutes for the telemetry other vendors collect.
How long is a Woven assessment?
Woven describes its scenarios as ranging from 90 to 120 minutes, built around real work such as reviewing a GitHub pull request or debugging a system. It is designed so that most candidates do not finish everything, and prioritisation is part of what gets scored.
Who grades a Woven assessment?
Two Certified Engineers score every submission against a detailed rubric, with ongoing coaching as scenarios and rubrics change. Results are returned within about a day. You get written commentary rather than only a number, which is unusually useful feedback for a screening step.
What are Woven's cheating statistics?
Woven publishes three figures: one in ten developers cheat on a technical assessment or take-home with a tool like Claude, Cursor or ChatGPT; those who do so without proctoring are three times more likely to advance; and therefore about one in three interviews at unproctored companies is with someone who cheated. These are vendor figures from a company selling proctoring, and the third is a derivation rather than a measurement.
Can Woven tell the difference between using Stack Overflow and using AI?
Woven says explicitly that its reviewers must distinguish acceptable practice, such as consulting Stack Overflow, from cheating where the skill being measured was never exercised. That is a human judgement rather than a threshold, which is both the strength and the limitation of the approach.
See also
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