ASSESSMENT STUDIO

See the work.
Understand the result.

Design practical assessments with controlled timing, consent-led proctoring, deterministic checkpoints, AI-assisted first-pass feedback, and human-reviewed outcomes.

Design an assessment
01 / REAL WORK

Move beyond generic questions.

Valases can place candidates inside the tools and evidence patterns used by the role.

  • Spreadsheet tasks with cells, formulas, and workbook evidence
  • Coding exercises with language choice and starter code
  • Accounting and close simulations
  • Individual and corporate tax scenarios
  • Business cases with source documents and written judgment
A professional completing a spreadsheet and coding work sample
TASK-BASED ASSESSMENTEvidence created through work
02 / CONTROLS

Designed around time, integrity, and review.

Every assessment can communicate expectations clearly while protecting the evidence needed by the hiring team.

T

Time-centric delivery

Use whole-assessment or per-question timing, configured duration, availability windows, visible countdowns, and secure attempt state.

P

Consent-led proctoring

Run camera and environment preflight, then use AI-assisted phone, gaze, and multiple-person signals alongside session events for human review.

AI

AI-assisted first review

Generate rubric-aware first-pass feedback on submitted work so reviewers can validate, edit, reject, or expand it before an outcome is recorded.

S

Explainable scoring

Score MCQs with clear keys and task environments with weighted checkpoints, tolerances, expected values, and recorded reviewer changes.

B

Assessment builder

Create, preview, validate, publish, version, duplicate, archive, and reuse role-relevant assessment definitions.

D

Secure delivery

Issue candidate-specific links with expiration, resend and revoke controls, autosave, recovery, and duplicate-safe submission.

R

Reviewer workspace

Inspect answers, task evidence, checkpoint matches, activity events, advisory integrity signals, and override reasons in context.

03 / HUMAN CONTROL

AI assists the review.
People own the outcome.

AI-generated feedback and advisory proctoring signals remain review inputs, not final scores or employment decisions. Reviewers validate the evidence, interpret context, and remain responsible for the outcome.