Start technical interviews without waiting for an engineer.
Invite candidates, follow interview status, and send reviewers a structured evidence report only when their judgment is needed.
Open workspaceControlled technical interviews in a real project
See how candidates work, not just what they submit.
UniCheck.AI runs a role-specific interview and preserves the observable working path inside an isolated workspace. AI organizes the material for review; your team makes the decision.
Screen and code synchronized · Optional camera with consent · Human decision
candidate-project
Environment ready
▾ src
● payment.ts
▾ tests
● payment.spec.ts
payment.ts
Workspace initialized
01
async function capturePayment() {
02const payment = await lock(id);
03await repository.save(payment);
04expect(result.status).toBe("paid");
05}
Focused tests completed12 passed · 1 review signal
Observed timeline
Review stateWorkspace is ready
Working project
Observable path
Role-specific AI policy
Manual review
Human decision
A technical interview—not a coding puzzle
Assess skills in a real project under the rules of the actual role.
The interview starts from a real engineering problem inside an existing project: code, dependencies, tests, constraints, and trade-offs. Before the invitation, the team also defines whether AI is allowed and which tools the candidate may use.
Review strong decisions and questionable steps through observed actions.
Connect code changes, tests, explanations, and permitted tool use with the way the candidate validates and defends the final solution.
Open workspaceReplace repeated first-round interviews with one reviewable process.
Pilot one role, compare the report with expert judgment, and measure engineering time saved before expanding the workflow.
Open workspaceFrom role to reviewable evidence
Do not ask reviewers to trust a score they cannot inspect.
UniCheck.AI links each conclusion to the candidate's work and keeps uncertainty visible. AI helps organize the evidence; it does not silently hire or reject anyone.
Role brief
The stack, level, constraints, and review criteria are agreed before the interview starts.
Interview project
The candidate enters a working codebase with a realistic engineering problem—not an algorithm quiz.
Work session
The AI policy is set before the invitation; changes, tests, and explanations create a reviewable working path.
Evidence report
Each finding points to an observed artifact and separates facts from signals that need review.
Human decision
Recruiters and engineers decide who advances and where a short follow-up is still useful.
Controlled interview workspace
Reconstruct the working path on one synchronized timeline.
UniCheck.AI runs the interview in an isolated workspace and brings screen activity, code changes, opened files, tests, commands, and workspace events into one reviewable timeline.
- 01
Screen and code chronologySee what changed and when.
- 02
Files, tests, and commandsFollow the working path in context.
- 03
Optional camera recordingEnabled with candidate notice and consent.
A signal is context for human review, not an automatic accusation.
Camera optionalConsent required
11:42:08Transaction boundary updatedsrc/services/payment.ts
11:47:31Focused test addedtests/payment.spec.ts
11:51:06Implementation refined4 lines added · 2 removed
▾candidate-project
▾src
•payment.tsedited
▾tests
•payment.spec.tsopened
11:40Workspace startedEnvironment ready
11:47Test command completed12 passed · 1 failed
11:53Approach changedContext saved for review
Session timelineScreen and workspace events aligned
Started
Code changed
Tests run
Review context
AI-use policy
Allow AI where the real role requires it.
For every interview, the team defines an AI-use policy and shows it to the candidate before the session begins. UniCheck.AI helps reviewers assess the quality of engineering work with the output, not the mere fact that a tool was used.
Open your workspace
What the candidate sees
AI tools are not allowed. Complete the task independently inside the interview workspace.
Editor, terminal, and project documentation
Screen, code, files, tests, and commands inside the interview workspace
The engineering path and any signals that may require a manual policy review
- 01
ApproachIndependent problem analysis
- 02
ValidationSolution checked with tests
- 03
OutcomeChanges linked to the working path
Session outcomeEvidence ready for human review
Less coordination. Better technical context.
Give each person the detail they need.
Keep the pipeline moving without chasing interview slots.
See who started, who completed the interview, which report is ready, and where a technical reviewer needs to step in.
See how the candidate reasons and works with permitted AI.
See how the candidate frames the problem, validates the answer, corrects errors, and integrates the result into the project. Keep live discussion for uncertain choices and engineering trade-offs.
Measure the workflow before committing to scale.
Compare report quality with expert assessment, track reviewer hours, and decide whether to expand after a scoped pilot.
Transparent rules and human review
Candidates know what is allowed and what is recorded.
Before the invitation, the team defines one consistent policy: which tools are available, which actions are recorded, and who can review the material. Camera recording is enabled separately, with candidate notice and consent.
Discuss trust, consent, and retention →Does UniCheck.AI hire or reject candidates?
No. It organizes evidence and recommends a review path. The hiring team owns the decision.
What is an AI-enabled task?
It is a working project where AI use is part of the assignment itself. The candidate must deliver a working result, validate the tool's suggestions, and explain the engineering decisions behind it.
Does session control prove candidate identity or misconduct?
No single signal proves misconduct. Screen activity, code history, files, tests, commands, and other configured session events are presented for manual review. The hiring team interprets the context.
How do camera recording, notice, and retention work?
Camera recording is optional and is enabled only for a configured interview with candidate notice and consent. Access and retention should follow the hiring organization's approved policy.
Can candidates use AI during the interview?
Yes. Each interview uses one of three modes: no AI, AI allowed, or an AI-enabled task. The same policy is shown to every candidate before the session. Reviewers assess how the candidate validates and improves the result, not the mere fact that a tool was used.
Two ways to get started
Explore UniCheck.AI on your own or with our team.
Open a completed interview in the demo workspace, or request a guided walkthrough tailored to your roles, AI policy, and session-control requirements.
Open the demo workspace and inspect a completed interview.
Review the report, session evidence, and assessment workflow at your own pace.
01Explore a completed interview
02Review session control and permitted AI use
03Create an interview for your own role
Request a guided demo for your hiring workflow.
We will show the product against your role types and help define a focused pilot.
01Review your roles and current hiring process
02Walk through AI policy and session control
03Agree on pilot criteria and the next step