Riskiy
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Applicant Retention Intelligence

Turn hiring activity into retention insight.

Riskiy helps recruiting teams organize applicants, track hiring stages, capture outcomes, and learn which job-related signals historically correlate with early turnover inside their own pipelines.

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  • Outcome-first retention scoring
  • Private company workspaces
  • CSV-first onboarding, no API required

Problems We Aim To Solve

Mass hiring teams need cleaner retention feedback.

Fragmented applicant data

CSV exports, resumes, ATS notes, and recruiter decisions often live in separate places.

Weak outcome tracking

Teams may know who was hired, but not whether that person stayed 14, 30, or 90 days.

One-size-fits-all assumptions

A signal can mean different things in seasonal retail, logistics, healthcare support, or call center roles.

How It Works

Start with client-owned data, then learn from outcomes.

1Import or enter applicants

Use CSV exports, resume uploads, or manual entry without waiting for perfect API integrations.

2Normalize job-related features

Keep raw uploads, extracted features, prior employers, and pipeline context auditable.

3Track hiring outcomes

Record hires, no-shows, quit dates, termination reasons, and retention milestones.

4Review evidence-backed patterns

Use pipeline-specific rules as decision support, not automated rejection.

Industries

Your workspace adapts to the industry you hire in.

Pick an industry during account creation and Riskiy pre-loads matching roles, pipelines, intake fields, and certification context across the app.

Pricing

Plans that scale with your hiring volume.

Every plan includes a private company workspace, transparent risk scoring, and retention outcome tracking. Checkout and billing run on Stripe.

FAQ

Important questions before using Riskiy.

Does Riskiy make hiring decisions?

No. Scores and rules are review prompts. Recruiters remain responsible for job-related, fair, and documented decisions.

What data should we start with?

CSV or spreadsheet exports from client-owned ATS, HR, payroll, and onboarding systems are the recommended MVP path.

What protected-trait data should not be collected?

Do not collect or infer protected traits such as race, gender, religion, disability, pregnancy, age, national origin, family status, or demographic proxies.

Why are outcomes so important?

Retention outcomes connect applicant features to real results. Without labeled outcomes, the product can organize data but cannot learn pipeline-specific patterns responsibly.

Can API integrations be added later?

Yes. Riskiy is structured so CSV, manual entry, document uploads, and future ATS APIs feed the same ingestion and normalization layer.

How does billing work?

Choose a plan, create your account, and complete checkout through Stripe. The subscription belongs to your company workspace, so teammates who join with your join code share the same plan.

Can we change or cancel the plan later?

Yes. Plans can be switched from the in-app billing screen at any time, and Stripe handles proration, payment methods, and cancellation.

Riskiy

Applicant Retention Intelligence

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Use your Riskiy account to access candidate data.

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Create Account

These setup fields tailor pipeline defaults without collecting protected traits.

Account access Password must be 12+ characters with an uppercase letter, number, and symbol.
Company workspace Create a private company workspace, or join an existing company with its join code.
Hiring context Riskiy uses this to prefill neutral workflow settings and reporting context.
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Reset Password

Enter a username or email. Local prototype mode returns a reset token directly on screen.

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Set New Password

Password must be 12+ characters with an uppercase letter, number, and symbol.

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Choose your plan

Activate your workspace

Pick a plan to unlock candidate tracking, imports, and retention analytics for your company workspace.

Applicant Retention Intelligence

Dashboard

Export CSV Add Candidate

Candidate Queue

Lower risk scores are better. Candidates are sorted from lowest risk to highest risk.

Candidate Role Risk Score Workflow Main Signal

Candidate Workspace

Filter, sort, compare, and clean up applicant records from one working view.
0-0 of 0

Add Candidate

Collect hiring data only when it is job-related. Do not collect protected-class or demographic proxy data.

Applicant and Workflow

Location and Logistics

Work History and Role Fit

Prior Employment History

Add one row per prior role. These rows are job-history facts used for tenure and role-context review.

Employer Role Industry City State Start End Reason

Healthcare Experience

Schedule and Application Behavior

Recruiter Notes

CSV, Excel, and Document Import

Client-owned exports and uploaded files feed the same normalization pipeline.

Drop CSVs, Excel workbooks, resumes, or documents here CSV and Excel create full candidate rows. Multiple PDF, DOCX, DOC, and TXT files create one review row per document.
Download Template

Data Source Layer

Active source paths and future connectors share one ingestion audit trail.

Connector Readiness

CSV remains primary while ATS and HRIS APIs stay pluggable.

Recent Ingestion Runs

Audit trail for CSV, document, manual, and future API source activity.

Review Import

Check parsed fields, correct anything that looks off, then save the reviewed candidates.

Pay-rate review Riskiy only imports compensation when it sees explicit pay context. Implausible values or contact numbers are left blank for recruiter review.
Import Source Name Role Pipeline Industry City State Pay Rate Warnings

Restricted

Admin access required

Data Audit and Architecture are hidden for non-admin accounts because they contain sensitive source, tenant, and system diagnostics.

Predicted vs Actual

Update outcomes after hire decisions and retention milestones.

Candidate Risk Score Stage Actual Outcome Notes

Risk Score Model

0 means lowest risk. 100 means highest risk. Scores are review prompts, not automatic decisions.

Data Transparency

What Riskiy uses and what it intentionally excludes.

Dynamic Applicant Model

Applicant-wide consistencies and labeled outcomes recalibrate review support.

Evidence-Based Rules

Pipeline and context-specific patterns generated from observed hiring outcomes.