G
ATS / Recruiting

Greenhouse AI Integration

Connect Greenhouse to BeforeQuery for grounded AI answers and agent actions across ATS / Recruiting.

Connect Greenhouse
What is it?

About Greenhouse

Greenhouse is one of the ATS / Recruiting platforms BeforeQuery connects to. Once linked, the platform's data becomes a first-class source for grounded AI answers and a target for policy-gated agent actions — the same identity, approval, and audit-log guarantees every other integration ships with.

Setup

How to connect Greenhouse

  1. Step 01

    In the BeforeQuery dashboard, go to Integrations → ATS / Recruiting and select Greenhouse.

  2. Step 02

    Sign in to Greenhouse with an account that has permissions to grant BeforeQuery the ATS / Recruiting scopes required.

  3. Step 03

    Confirm the connection. Greenhouse is now available as a source and action target for every playbook in your workspace.

Explore

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How BeforeQuery uses Greenhouse

What the agent does with your Greenhouse connection

  • 01

    Read candidate pipelines from Greenhouse to give recruiters, hiring managers, and executives live status without opening the ATS.

  • 02

    Draft interview follow-ups, rejection emails, and candidate-experience touch-ups grounded in your interview notes and rubrics.

  • 03

    Auto-tag and route new Greenhouse candidates by skill match, seniority, or requisition fit.

  • 04

    Coordinate the panel: schedule interviews, send prep packets, collect scorecards — all triggered by Greenhouse stage transitions.

Use cases

What teams actually do with the Greenhouse integration

Interview-stage automation

When a candidate advances to on-site in Greenhouse, a playbook drafts the calendar invites for the panel, sends the candidate a prep packet with your travel-and-logistics doc, and sets a scorecard-due reminder for interviewers 24 hours after the interview.

Rejection email drafts grounded in interview notes

When a candidate is moved to "rejected" in Greenhouse, BeforeQuery drafts a personalized rejection email that references the specific stage they reached and (optionally, per your policy) high-level feedback — without exposing individual interviewer notes.

Pipeline health digest

Weekly summary of Greenhouse pipeline movement — new candidates per req, stage-conversion rates, time-in-stage anomalies, upcoming interviews. Delivered to hiring managers in Slack; drill-down back to Greenhouse on click.

Answer questions grounded in Greenhouse

Employees and customers ask Greenhouse-related questions in Slack, Teams, or the widget — BeforeQuery answers with the exact Greenhouse record shown alongside the response. No context switching, no "log into ATS / Recruiting to check" round-trips.

Greenhouse — Frequently Asked Questions

Common questions about connecting BeforeQuery to Greenhouse.

Yes, gated by your approval matrix. Stage-forward moves (schedule interview, extend offer) are typically approver-required; stage-back moves (reject, hold) can be autopilot with a reason logged. All moves reversible via the audit trail.
No — BeforeQuery is read-and-write scoped, not a ranking replacement. Your ATS's own scoring is untouched. BeforeQuery draws on the same data to answer questions, draft communications, and orchestrate downstream actions.
Standard OAuth 2.0 where Greenhouse supports it, otherwise API-key or bearer-token auth. Credentials are stored encrypted at rest (AES-256-GCM) per workspace, never shared across customers, and rotated on request. The connection is scoped to the least-privilege set of scopes each playbook needs — you approve the scope list on install.
No. Your Greenhouse data feeds only your workspace's own agents and answers. Nothing is used to train a shared model, and nothing crosses workspace boundaries. Bring-your-own-model is available on Enterprise if you want to pin inference to your own OpenAI / Anthropic / self-hosted deployment.
Yes. Every Greenhouse integration is scoped at install time — you pick which resources, users, or record types are visible. You can further restrict per-playbook: a single playbook only touches the specific Greenhouse objects it needs. Scope changes take effect on the next sync.
Every write is logged with the acting user, the playbook that fired it, the exact operation, the target entity IDs, and the timestamp — all in the immutable audit log. Writes are rehearsable in simulation mode against a copy of live data before they touch Greenhouse for real.

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