Read this one
sceptically.
We sell one of the things on this page, so treat it as an argument rather than a review. What we can offer is a comparison that does not pretend the alternatives are bad: every platform here gets a section on what it does better than us, and those sections are the reason this page is worth reading at all.
Checked 19 September 2026. All five shipped AI features within about a year, so verify anything that matters with the vendor before deciding.
The interesting question is no longer whether AI is allowed
A year ago that was the dividing line. It is not any more. Every platform below now runs an AI-assisted format and shows a reviewer what the candidate actually asked for.
So "we let candidates use AI" no longer tells you anything, and neither does "we show you the prompts". The questions that still separate these products are narrower: does anything turn that transcript into a judgement, does that judgement point at specific moments, and what happens when the moment it points at turns out to be wrong.
What each one captures, and whether it scores it
| Platform | AI in the assessment | What the reviewer sees | Scores how AI was used? |
|---|---|---|---|
| HackerRank | AI Fluency Evaluation, plus repository tasks where a candidate resolves a ticket | IDE activity across the assessment and the full candidate–AI conversation | Yes — letter grades on context quality, critical thinking and collaboration, with reference links into the transcript |
| CodeSignal | Agentic assessments built around Claude Code, Cursor and Codex, plus their Cosmo assistant | Full transcript of the candidate–AI interaction, plus session replay | Not as a separate published score |
| Codility | Cody, their assistant, inside a VSCode environment | Every prompt, suggestion and follow-up, as reviewable activity | Deliberately not — AI activity does not affect their automated scoring |
| CoderPad | AI Assist enabled by default on all pads, with Ask, Edit and Plan modes | Logged AI Assist usage, a transcript and notes | Partly — the modes are framed around how a candidate writes and reasons with AI |
| HackerEarth | VibeCode Arena | How a candidate frames a prompt, iterates, and validates the output | Yes — rubric-scored |
| codesolara | A real workspace with an assistant, on a task from the platform or your own library | Prompts, edits, commands and their output, as the evidence behind each score | Yes — against authored bands, with a second pass that re-checks every citation |
Each platform name links to a fuller comparison. Sources for every competitor row are recorded internally with where each claim came from — ask and we will send them.
Reasons to choose one of them instead
Written so that an engineer who works there would call it fair.
The largest problem library in the category, the strongest name recognition with candidates, and the deepest set of ATS integrations. Their AI fluency grading also links each dimension back to the excerpt behind it, which is the closest thing to our own approach that anyone ships.
Candidates work in the agentic tools they already use rather than a built-in chat panel, which makes the exercise closer to the real job than anything else here. Session replay is genuinely useful for a reviewer who wants to watch rather than read, and they run at enterprise scale we do not.
That refusal is a defensible position and arguably more honest than a shaky automated number: they capture the evidence and leave the judgement to a human. If you distrust automated assessment of AI collaboration on principle, they have already agreed with you.
The best live, human-in-the-room interview experience of the five, with the least setup. Candidates choose among several current models, and AI being on by default means the awkward "are we allowing it" conversation never has to happen.
They score people and AI models against the same rubric, which is a genuinely original idea and gives a reference point nobody else offers. Strong for running this at volume, and for internal capability programmes rather than only hiring.
One difference, and it is narrow on purpose
Given the table above, we are not going to claim a long list. There is essentially one thing, and it only matters if you care about defending a decision later.
- A second pass re-checks the evidence. A separate run takes each criterion's citations and confirms they say what the score claimed. When they do not, the criterion is withdrawn rather than marked down — an invented citation must not cost a candidate marks, and it must not earn them either.The reasoning, in full.
- When that check does not run, the card says so. An unverified result that looks identical to a verified one is the failure worth designing against hardest, because it is invisible by construction.
- Bands are authored before anything is scored. Someone writes down what high, middle and low look like for the role — all three. A letter grade positioned as supplementary is a hedge, and it is a hedge because an unexplained letter cannot carry a rejection.
- Probes run the submission. A probe that fails is a mark against the work. A probe that errored is a grading failure, reported as one rather than folded into a low score.
Cases where we are the wrong answer
A comparison page without this section is a brochure.
- You need to filter hundreds of applications cheaply. Verification is a second model run, so it is slower and costs more per candidate. For a first cut at the top of a funnel, that is the wrong shape and the incumbents are better at it.
- A certification is a hard requirement. We do not hold SOC 2, ISO 27001 or any third-party certification today. Several platforms above do. If that gates your procurement, it gates it.
- You want a large ready-made problem library. Ours is small and deliberately so — every problem has to fail a clean-agent baseline before it ships. If you want thousands of questions on day one, that is not us.
- You want candidates to recognise the brand. They will not. That is a real cost in candidate experience and we are not going to pretend otherwise.