Technical Assessment
AI-generated, job-calibrated technical tests — MCQ, short answer, scenarios, and code questions — locked to your real applicants, scored into your pipeline, no separate assessment vendor needed.
Between "the CV looks right" and "let's spend an hour of the panel's time" sits the most expensive gap in most hiring pipelines: nobody has verified that the candidate can actually do the work. Teams traditionally close it by bolting on a standalone testing platform — another vendor, another per-candidate fee, another login for candidates, and results that live outside the system where the hiring decision is actually made. Expertini ATS closes the same gap natively: the Technical Assessment tool builds a mixed-format test from one of your real job openings, sends it only to candidates who applied, and writes every score straight onto the candidate's application in your hiring pipeline.
The test itself is generated by AI from the job's actual description — not a generic question bank. Ask for anywhere from 5 to 50 questions and you get a calibrated mix: roughly 40% multiple-choice, 20% short answer, 20% realistic scenario questions, and 20% code-reading or code-writing questions appropriate to the role's stack and seniority. Multiple-choice answers score themselves the instant a candidate submits; open answers can be scored by your team for free, or reviewed by AI against per-question marking guidance.
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- How it fills the pipeline gap — a typical flow
- Locked to real applicants — and that lock is the feature
- Question integrity and honest scoring
- What it costs — and what it doesn't
- Architecture: where it sits in the platform
- Data model and dependency map
- Operational considerations
- Interaction contract
- Interface blueprint & interaction flow
- Frequently asked questions
01How it fills the pipeline gap — a typical flow
Take a Python Developer opening with 34 applicants. CMS scoring narrows the field to twelve on documented evidence; but a CV can claim FastAPI experience without ever having handled a dependency-injection question. From the assessment page you pick the job (type-to-search across your own openings), generate a 15-question test calibrated to its real description, review and edit any question — then invite exactly those twelve candidates from a pipeline picker. Each gets a branded email; each takes the test in the browser with no account to create; MCQs are scored on submit and every result lands on the candidate's application row. The eight who clear your bar move to the interview stage with their score already attached — the gap between "looks right" and "verified" closed in an afternoon, without a single external tool.
02Locked to real applicants — and that lock is the feature
An assessment link that anyone can take produces results you can't trust and can't file anywhere. Expertini locks every assessment to candidates who actually applied to the linked job: the candidate must start with the same email address they applied with, and anyone else is asked to apply first. That lock is exactly what makes the results pipeline-native — because every attempt belongs to a known application, the score appears on the candidate's application report, in stage-by-stage pipeline views, and in the candidate's transparent audit report PDF alongside CMS scores and interview feedback. When someone asks "why did we advance this candidate?", the answer is one document, not four vendor dashboards.
03Question integrity and honest scoring
Once the first candidate has answered, the question set locks — the test stays exactly as answered, which is what keeps responses comparable and the record auditable. Candidates never see correct answers or marking guidance; those exist only on the HR side. Scoring is layered honestly: machine-checkable questions auto-score deterministically, open answers show the candidate's verbatim response next to your marking guidance, and you choose per attempt whether to score manually (free) or let AI propose per-question scores and a summary you can override. The final score is always auto + review — never a black-box verdict.
04What it costs — and what it doesn't
Generation uses 3 AI prompt credits from your plan's monthly allowance and AI review of one attempt uses 2 — manual scoring, custom hand-written questionnaires, candidate invites, and unlimited retake management cost nothing. There is no per-candidate fee, no per-test fee, and no separate assessment-vendor subscription: a standalone testing platform typically bills per candidate or per month on top of your ATS, while here the capability ships inside the same plan you already have. To protect your credits, tests can only be generated against a real job in your account.
Platform architecture & operations
A1Architecture: where it sits in the platform
Technical Assessment is a first-class module of the Interviewing suite inside the authenticated Expertini ATS workspace. The platform is deliberately server-rendered: every view is prepared by the application server and shipped as complete HTML, with no client-side framework, no third-party CDN scripts, and no build pipeline between the data and the page. What renders is what the server computed — the property that makes the interface auditable.
All persistence runs on a single search-native document store; every query carries the organisation's identifier as a mandatory filter at the lowest query layer. Tenant isolation is therefore structural — a property of how every request is composed — rather than a policy that relies on application code remembering to check.
Availability is governed by the platform's tool registry: this tool is registered from the Growth plan, and access is enforced server-side by the registry gate on every request — never by hiding a button. Plans also carry a monthly distinct-tool quota (3 / 5 / 15 / 30 / 45 across Trial→Business, unlimited on Enterprise), counted at the same chokepoint. The pricing page states both honestly: what is available, and how much of it the month includes.
A2Data model and dependency map
In production the tool reads and writes assessment definitions (ats_assessments), assessment attempts (ats_assessment_attempts). Documents are plain, explicitly-mapped fields — mappings are provisioned ahead of first write, so term filters and aggregations behave deterministically instead of depending on inferred types.
Every distinct open is journalled to the tool-activity store — and that journal, not a parallel analytics system, is what the Reports section aggregates. The usage numbers you see are the numbers the platform actually recorded.
Anything that leaves the request path — notification fan-out, webhook delivery, activity journalling, mail — runs in fire-and-forget background threads. A slow external endpoint can never make the interface hang, and a failed side effect is logged rather than silently retried into inconsistency.
A3Operational considerations
Organisation-level settings, destructive actions, and connections are gated to owner and admin roles; recruiters operate the tool on the records they can see. Role changes apply on the next request — enforcement is at the route, not in the menu.
Failures are surfaced, not swallowed: server-side validation returns the exact field and reason, vendor errors are quoted verbatim where integrations are involved, and every write either confirms or reports. Exports regenerate on request rather than being cached — a report you download reflects the store at the moment you asked, not last night's snapshot.
Everything written is yours to take: CSV exports and the Data Export app cover the same stores the product itself reads. The exit is as open as the entrance — by design, not concession.
A4Interaction contract
The interface follows the platform's search-and-select convention: any field that names a real record — a candidate, client, or job — is a type-to-search picker over live data, never a free-typed string, which is what keeps activity trails and deduplication trustworthy. Static choices are filter-as-you-type combos rather than native dropdowns, and state transitions give explicit feedback: server confirmations surface as toasts, validation errors name the exact field, and nothing is shown as done that the server has not confirmed.
The wireframe and flow below document the structural contract of the surface — what panels exist, what order the states occur in, and what happens at every edge — rather than pixels. The layout is composed with native CSS grid and flexbox and adapts from wide desktop to a single column without separate mobile views.
Dependency map
Interface blueprint
Interaction flow — states, validations, feedback
Neighbouring tools — Interviewing
Frequently asked questions
Can anyone with the link take the assessment?⌄
Do I need a separate assessment platform subscription?⌄
What does it cost in credits?⌄
Can I edit the AI's questions?⌄
Where do the results show up?⌄
At a glance
- AI-generated from your real job description — never a generic question bank
- Locked to applicants: results always belong to a real application
- Invite candidates by email straight from the job's pipeline
- MCQs auto-score instantly; open answers scored manually (free) or by AI
- Question set locks once answered — auditable, comparable responses
- No per-candidate fees, no separate assessment vendor
See technical assessment on your own hiring.
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