Hallo + Greenhouse: AI scenario-based language assessments in 56 languages with CEFR and estimated ACTFL scores

Hallo’s integration with Greenhouse automates language proficiency assessments inside your existing hiring workflow, delivering CEFR-based scores and feedback without manual interviews or external scheduling. This article explains what the integration does, who benefits most, how it works technically and operationally, the measurable advantages, and practical best practices for recruiters using Hallo with Greenhouse.

At a glance: Hallo uses AI-driven, scenario-based spoken and written prompts to evaluate candidates in 56 languages, returns CEFR and estimated ACTFL proficiency scores within minutes, and pushes results into Greenhouse so recruiters can make faster, evidence-based shortlisting decisions. Below you’ll find feature details, integration flow, implementation guidance, example workflows, ROI considerations, and common questions to help determine whether Hallo + Greenhouse fits your hiring stack.

Core capabilities of Hallo for Greenhouse

• AI-driven spoken and written assessments Candidates respond to real-world prompts via mobile or web; Hallo uses AI to evaluate fluency, vocabulary, grammar, pronunciation and coherence.
• CEFR and ACTFL-aligned scoring Results map to CEFR levels (A1–C2) and provide estimated ACTFL equivalence plus detailed feedback per skill area.
• Fast, scalable testing Typical test completion under 10 minutes; ideal for screening hundreds or thousands of applicants without adding interviewer hours.
• Seamless Greenhouse integration Invitations, results, and score reports flow directly into candidate profiles or scorecards, preserving your existing workflow.
• Admin dashboard and exports Central results page with filters, bulk exports, and role-based admin invites for easy operations and record keeping.

Integration behavior: once configured, Hallo can be invoked from stage actions or as an automated screening step in Greenhouse. When a candidate reaches the configured stage, Greenhouse triggers an invite; the candidate completes the test; Hallo returns the score back to the candidate’s Greenhouse profile and generates a PDF score report for review and archiving. This automated data transfer reduces manual steps and ensures assessment data is consistently available where recruiters already evaluate candidates.

Who should consider Hallo + Greenhouse

• Global hiring teams Organizations sourcing talent across regions that need fast, consistent language screening for many candidates.
• Roles requiring verified language ability Customer support, sales, localization, content moderation, or any role where spoken or written language accuracy affects performance.
• High-volume hiring operations Companies that need scalable assessments to avoid bottlenecks in interviewer availability and reduce per-candidate screening time.
• Compliance- and documentation-focused teams Teams that require standardised, auditable evidence of candidate language ability for regulatory or contractual reasons.

Typical assessment workflow and responsibilities

Accuracy and validation: Hallo reports a 95% accuracy rate compared to human-rated proficiency interviews (per vendor validation). Scores are accompanied by skill-level feedback (fluency, pronunciation, etc.), enabling recruiters to interpret borderline cases or request further evaluation when necessary. Because the scoring is fully automated, inter-rater variability is eliminated and assessments remain consistent across large applicant pools — a major advantage when scaling language screening.

Admin dashboard: practical capabilities

• Single-page results management View all candidate scores, filter by job, language, or score range, and quickly identify top language performers.
• Bulk export and reporting Export score sheets and PDFs for hiring managers or compliance records with one click.
• Role-based access Invite unlimited admins and set permissions so hiring managers see only relevant data.

Language coverage overview

Implementation notes and technical requirements: Hallo’s Greenhouse integration does not require a partner implementation fee and is designed to be plug-and-play—most customers configure it through Greenhouse’s integration marketplace and set stage-based triggers. Basic prerequisites include a Hallo account, API connection settings, and admin permissions in Greenhouse to enable the webhook/actions. Plan for a short setup window: configuration, template invites, and a test run typically take a few hours to a day depending on internal approval cycles.

Security and privacy considerations: Hallo provides candidate data exports and stores assessment results; review Hallo’s privacy policy and Greenhouse’s support documentation to align with your data retention and access policies. For regulated industries, ensure you map storage locations and retention periods to your compliance needs before rolling out at scale. Where necessary, configure role-based access and limit exported reports to only essential reviewers to reduce exposure of identifiable candidate information.

Best practices for recruiters using Hallo with Greenhouse

• Define language thresholds per role Set explicit CEFR cutoffs in job profiles (e.g., B2 for client-facing roles) so screening becomes objective and repeatable.
• Embed the test early in the funnel Trigger the assessment at an initial screening stage to avoid wasting interviewer time on unqualified candidates.
• Communicate clear instructions Include example prompts and time expectations in the invite to maximize completion rates and performance accuracy.
• Combine scores with role-specific tasks Use Hallo scores together with work samples or technical tests to get a holistic view of candidate capability.

Example ROI scenario: if a recruiting team screens 2,000 applicants annually for language-sensitive roles and each manual phone screen consumes 20 minutes of interviewer time, automating with Hallo reduces interviewer hours significantly. At scale, reduced interviewer time plus faster shortlisting often translates to faster time-to-offer and lower per-hire screening costs. Metrics to track after implementation: assessment completion rate, average time-to-score, percentage of candidates meeting threshold, and recruiter time saved per hire.

Common questions about Hallo + Greenhouse integration

Hallo AI assessments vs. traditional human proficiency interviews