AI Built for Canadian Labour Relations

Labour relations should be human. AI should make it less bureaucratic — not less human.

Grounded in your collective agreement, your case evidence, and a curated Canadian labour relations corpus. Built on Anthropic Claude. AI assists; humans decide.

Cites the articles and provisions it relies on, so reviewers can verify the reasoning.

Built by the editor of Canadian Labour Arbitration (Brown & Beatty) — the reference text Canadian arbitrators cite.

Where AI Shows Up in Sertus

AI is woven into the labour relations workflow you already run — never as a black box, always anchored to the documents and facts in your account.

Across Your Workflow

  • Case assessment

    Strengths, weaknesses, risks, and recommended approaches surfaced for every grievance.

  • Scenario checker

    Test a discipline, policy change, or termination against the agreement before it becomes a grievance.

  • Agreement chat

    Ask natural-language questions across your collective agreements and get answers tied to specific articles.

  • Complaint analysis

    Informal complaints assessed against the agreement early — before they escalate to formal grievances.

Grounded in What Matters

  • Your collective agreement

    The actual agreement uploaded to your account, parsed into articles and clauses.

  • Your case evidence and history

    The grievance record, evidence, notes, and outcomes inside your organization.

  • Sertus’s Canadian labour corpus

    An original, proprietary corpus of Canadian labour relations content authored by co-founder Adam Beatty for the Sertus platform.

  • Built on Anthropic Claude

    Sertus uses Claude models accessed via the Anthropic API — selected for safety, factual grounding, and long-document analysis.

  • Not generic web data

    AI reasoning does not depend on open-web sources for labour relations content.

What Sertus AI Will and Won't Do

Clear lines, set on purpose. AI accelerates the analysis; your team makes the calls.

AI Will

  • Surface strengths and risks

    Identify strengths, weaknesses, and risks from both sides of a grievance.

  • Pinpoint applicable articles

    Identify the specific articles and provisions of your agreement that apply.

  • Cite every conclusion

    Cite the source for each conclusion so reviewers can verify the reasoning.

  • Cross-reference past cases

    Cross-reference similar past grievances inside your organization.

AI Won't

  • Train on your data

    Anthropic does not use customer inputs or outputs to train its models.

  • Make automated decisions

    No automated decisions about a worker, a grievance, or a discipline matter.

  • Act on its own

    Never sends correspondence, files a grievance, or executes an outcome without a human.

  • Reach across organizations

    Every AI request is scoped to the authenticated user's organization.

  • Reason from the open web

    Does not draw labour relations conclusions from generic web content.

Built for Sensitive Records

AI safeguards sit on top of the same security posture Sertus applies to every grievance and document.

AI Safeguards

  • Canadian data residency

    Customer data stored in Canadian cloud regions; AI inference disclosed on the sub-processor list.

  • PIPEDA-aligned handling

    Designed against PIPEDA principles for Canadian personal information.

  • Single sign-on (SSO)

    Centrally managed and revoked through your identity provider.

  • Append-only audit trail

    Sign-ins, grievance lifecycle changes, document access, and administrative actions recorded with timestamp and actor.

See Sertus AI on Your Own Case

Book a 30-minute demo. We'll walk through how AI handles a sample grievance against a real collective agreement — and show how the safeguards work in practice.

Last updated: May 2026