Greenhouse is a recruiting platform built around applicant tracking, structured interview plans, scorecards, scheduling, reporting, and an integration ecosystem. It is a strong candidate for organizations willing to standardize their hiring process. It does not make hiring fair or legally compliant on its own, and its newer AI and Model Context Protocol features require separate governance.

This review was checked on September 14, 2026. Greenhouse publishes package contents but not standard list prices.

Current packages and scope

The Greenhouse pricing page lists Core, Plus, and Pro packages. Core includes applicant tracking, structured interview kits and scorecards, scheduling, reporting, single sign-on, AI Notetaker, and Talent Matching. Plus adds capabilities such as sourcing automation, texting, a business-intelligence connector, AI report filters, and spam or fraud tools. Pro adds enterprise data configuration, an audit log, sandbox and synchronization options, and expanded recruiting CRM use.

Those are Greenhouse’s current package descriptions. A quote should identify included modules, implementation, environments, support, API or connector entitlements, AI usage, and renewal terms. A sales demonstration may include features outside the proposed tier.

Greenhouse is best suited to a recruiting organization that can define stages, interviewer responsibilities, decision criteria, and data hygiene. The system will not repair an unclear hiring model. Teams that configure many exceptions can reproduce their old process in a more expensive tool.

Structured hiring is a method, not an outcome guarantee

Interview plans and scorecards can make expectations explicit and create a record of evidence. Their quality still depends on job-related criteria, interviewer training, completion discipline, and monitoring of outcomes.

The US Equal Employment Opportunity Commission’s guidance on employment tests and selection procedures explains that neutral-looking selection tools can create unlawful disparate impact and that employers remain responsible for their procedures. The guidance does not evaluate or endorse Greenhouse.

During a pilot, inspect whether interviewers can see one another’s scores before submitting, whether required evidence is enforced, how late changes appear in the audit trail, and whether reports can compare stage progression and selection rates. Legal review should focus on the actual process, not the structured label.

AI features require product-level controls

Greenhouse’s AI addendum states that AI features are optional, may change, may have usage limits or extra fees, and require customer responsibilities. Contract language matters more than broad marketing claims.

Create an inventory of every AI function used in sourcing, matching, note-taking, filtering, drafting, or reporting. For each one, document input data, output, model provider, retention, human reviewer, permitted decision, and fallback. Test hallucinations, accent and language handling, sensitive-data leakage, and whether a user can challenge or correct a generated record.

New York City’s automated employment decision tools page provides official information about Local Law 144. Whether a specific Greenhouse configuration is covered depends on how it is used. Buyers should obtain advice for the relevant jurisdiction and keep deployment evidence.

MCP is an integration surface, not a blanket agent permission

Greenhouse describes Greenhouse MCP as an open beta for Site Admins on newer tiers, allowing approved AI tools to access Greenhouse through permissions. The open-beta status is a material qualification. It does not promise production availability, a particular service level, or safety for autonomous actions.

If tested, use a nonproduction environment, a dedicated identity, narrow read-only scopes, synthetic candidate data, and explicit approval for any write. Log queries and returned fields. Test prompt injection inside resumes and job descriptions. Confirm that revoking the identity removes access immediately.

Data protection and accountability

The Greenhouse master subscription agreement was updated in 2026 and should be read with the order form, data processing terms, and AI addendum. The customer remains responsible for its hiring practices and lawful instructions.

Request current subprocessors, hosting and transfer details, security assurance reports, retention controls, backup and recovery objectives, breach-notification language, and export formats. Restrict access to demographic, accommodation, interview-note, and offer data. Verify the audit record for viewing, exporting, editing, and deleting candidate information.

Decision checklist

  • Map required workflows and integrations to Core, Plus, or Pro.
  • Obtain a three-year quote including implementation, AI, environments, and renewals.
  • Pilot structured plans with real job criteria and trained interviewers.
  • Measure selection outcomes and investigate disparities.
  • Inventory each AI use and preserve human accountability.
  • Treat MCP as beta, start read-only, and test hostile content.
  • Validate privacy, audit, retention, export, and deletion controls.

Greenhouse can provide a disciplined hiring operating system when an organization is ready to govern the process. Its value is the consistency and evidence a team actually creates, not an assumption that an ATS, AI feature, or integration protocol guarantees better or fairer hiring.