Agentic hiring, with the guardrails in the product.
See how bounded agents, explainable recommendations, and full audit trails work across RippleHire's High-Performance AI ATS.
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RippleHire's agents run the machinery of hiring: scheduling, screening logistics, document checks, follow-ups. Recruiters decide who moves forward. Every agent is scoped, every recommendation is explainable, every action is logged.
ISO 27001. SOC 2 Type II. GDPR. 86M+ candidates across 50+ countries.

Your security review asks where the data goes. Legal asks who is accountable for a rejection. Your board asks what happens when a candidate challenges an outcome. None of those questions are answered by a page of principles.
RippleHire answers them with product behaviour you can inspect: agent permissions your admin sets, reasoning attached to every recommendation, and an exportable log of what each agent did and when. 86M+ candidates processed across 50+ countries, under controls audited to ISO 27001 and SOC 2 Type II.
We draw one line and hold it: agents own coordination, people own judgment. Coordination is the logistics that consume a recruiter's day. Judgment is who advances and who gets the offer. Everything below enforces that line inside the product.
Responsible AI fails when it lives in a PDF that nobody opens. In RippleHire it lives in configuration your team owns, which means the answer to "who approved this" is always a name and a timestamp.
Scope, permission, and escalation rules configured per agent in Agent Builder
Amy and the AI Voice Agent identify themselves as AI, with consent captured before recording
Recruiter overrides logged as their own events, which is what makes bias monitoring possible over time
Shield and the Document Validation Agent surface fraud and verification signals as evidence for a human, never as an automatic rejection

Security and legal get their answers before the questionnaire arrives.
Every recommendation, override, and rejection carries its reasoning.
Clear disclosure, and a human on the other side of the outcome.
See how bounded agents, explainable recommendations, and full audit trails work across RippleHire's High-Performance AI ATS.

Our agents handle coordination and evidence-gathering while hiring decisions stay with your recruiters. In the product that shows up as bounded agent permissions, explainable recommendations, complete audit logs, and human checkpoints you configure.
No. Agents screen, verify, and rank against criteria your team defines, and show the reasoning. Advancing or rejecting a candidate is a human action recorded against a named user.
Sensitive attributes are excluded from the features used for matching and ranking, recommendations are explainable so recruiters can see what drove them, and every override is logged so patterns can be reviewed over time.
Yes. Amy and the AI Voice Agent identify themselves as AI at the start of the interaction, and consent is captured before any recording.
Your candidate data serves your hiring workflows. It is not used to train models shared with other customers.
Yes. Each recommendation shows matched and unmatched criteria with source evidence, and the record is exportable for audit.
AI used in employment decisions carries elevated obligations under the EU AI Act, and both GDPR and DPDP give candidates rights over their data. RippleHire supports these with human oversight of decisions, explainable outputs, audit logs, consent management, and configurable retention and erasure. Compliance obligations sit with you as the employer; we provide the controls and the records.
No. It is how the platform is built. Amy, Interview Copilot, the AI Voice Agent, Document Validation, Shield, and anything you build in Agent Builder run under the same controls, and none of it is purchased separately.