| Automated reference collection | Runs requests, invitations, reminders, progress updates, completion alerts, and summaries inside a reusable Flow. | Automates reference requests, email and SMS reminders, tracking, reporting, and candidate/referee administration. |
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| Conversational follow-ups | Jointl Intelligence can ask a relevant follow-up when an answer is vague, incomplete, or deserves a concrete example. | Uses configurable, static templates and custom questions without answer-triggered adaptive deep-dive follow-up questions. |
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| Reference types and role relevance | Supports configurable reference profiles and role-specific questions within each Flow. | Supports flexible templates and custom questions for reference workflows. |
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| Fraud and identity signals | Surfaces technical and behavioral risk signals across reference checks, invitations, assessments, emails, and response patterns; LinkedIn authentication can strengthen reference identity confidence. | Uses multiple fraud-detection data points and supports candidate or referee verification through options including Yoti, LinkedIn, passport, or a UK share code, depending on the workflow. |
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| Audit trail | Detailed workspace and evaluation activity can support accountability and review across the broader Flow. | A centralized audit trail covering reference-related text, email, and phone attempts. |
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| Pre-screening and assessments | Collects eligibility, preferences, documents, custom answers, assessments, and work-sample evidence before or alongside references. | Reference and selected screening forms without a unified dynamic assessment Flow. |
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| Matching and scoring | Matching Scores can combine assessments, requirements, references, custom attributes, and supported verification signals with rules and triggers. | Structured reference and screening reports without multi-source role Matching Scores, custom scoring models, or Flow triggers. |
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| Cross-source evidence | Cross-Verified Insights show when multiple named sources support a finding, while Single Profiles retain gaps, contradictions, and source context. | Centralized reference results and audit information without cross-verification across assessments, references, verifications, and employee signals. |
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| Talent pool | Talent Pool stores candidates, references, and useful contacts; Public Profiles and People Graph add consent-based public context and relationship mapping. | RefNow Talent asks referees whether they want to opt into the employer’s talent pool and lets recruiters search, contact, or export those leads. |
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| High-volume workflows | Bulk Import, Bulk Matching, Autopilot links, automated rules, and multi-company workspaces support high-volume evaluation. | Supports candidate uploads, automated reference processing, and a broad ATS/HRIS integration directory. |
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| Employee intelligence | | RefNow Respond reduces ex-employee reference administration; ongoing contribution and team-intelligence workflows sit outside that focus. |
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| AI and natural-language access | Compatible AI assistants can find authorized records, summarize evidence, compare people within one Flow, and prepare governed actions. | ATS/HRIS integrations and API access without direct MCP-based access through ChatGPT or Claude. |
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| ATS, HRIS, and API connectivity | Offers integrations, direct API access, MCP, and custom people intelligence layers. | Offers a large ATS/HRIS integration directory and API support for custom connections. |
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| Fair Unlimited Pricing at hyperscale | Unlimited Flows, applicants, pre-screening and data collection, assessments, conversational reference checks, Talent Pool contacts, Autopilots, employees, associated companies, users, templates and custom forms, Glow Moments, Team Pulse cycles, Exit Intelligence workflows, and Jointl control through ChatGPT and Claude. Scale from one workflow to high-volume, multi-company use without per-applicant friction across included core features. | No directly comparable unlimited model. Usage-based, package-based, per-applicant, per-check, credit-based, or negotiated pricing can increase total costs as volume grows and make broader, deeper evidence collection more expensive. |
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